From 281f2f29b796ffe22cc864d806f15e2c807ec08e Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Sat, 18 Aug 2018 16:09:59 -0700
Subject: [PATCH 01/13] replace DvBool with .NET standard bool type.

---
 src/Microsoft.ML.Api/ApiUtils.cs              |   2 +-
 .../DataViewConstructionUtils.cs              |  17 +--
 src/Microsoft.ML.Api/TypedCursor.cs           |  15 +--
 src/Microsoft.ML.Core/Data/ColumnType.cs      |   2 +-
 src/Microsoft.ML.Core/Data/DataKind.cs        |   4 +-
 src/Microsoft.ML.Core/Data/DvInt1.cs          |  66 +----------
 src/Microsoft.ML.Core/Data/DvInt2.cs          |  66 +----------
 src/Microsoft.ML.Core/Data/DvInt4.cs          |  66 +----------
 src/Microsoft.ML.Core/Data/DvInt8.cs          |  66 +----------
 src/Microsoft.ML.Core/Data/MetadataUtils.cs   |   6 +-
 src/Microsoft.ML.Core/Data/TypeUtils.cs       |  78 -------------
 .../Commands/TrainCommand.cs                  |   1 -
 src/Microsoft.ML.Data/Data/Conversion.cs      |  45 ++++----
 src/Microsoft.ML.Data/Data/RowCursorUtils.cs  |   8 +-
 .../DataLoadSave/Binary/CodecFactory.cs       |   4 -
 .../DataLoadSave/Binary/Codecs.cs             | 107 +++---------------
 .../Evaluators/BinaryClassifierEvaluator.cs   |  17 +--
 .../Evaluators/ClusteringEvaluator.cs         |   6 +-
 .../Evaluators/EvaluatorUtils.cs              |  28 ++---
 .../MultiOutputRegressionEvaluator.cs         |  22 ++--
 .../MulticlassClassifierEvaluator.cs          |   6 +-
 .../Evaluators/RankerEvaluator.cs             |   6 +-
 .../Evaluators/RegressionEvaluatorBase.cs     |   6 +-
 .../Scorers/BinaryClassifierScorer.cs         |   9 +-
 .../Scorers/ScoreMapperSchema.cs              |   6 +-
 .../Transforms/ConcatTransform.cs             |   6 +-
 .../Transforms/ConvertTransform.cs            |   2 +-
 .../Transforms/GenerateNumberTransform.cs     |   6 +-
 .../Transforms/KeyToVectorTransform.cs        |   2 +-
 .../Transforms/LabelIndicatorTransform.cs     |   8 +-
 .../Transforms/NormalizeColumn.cs             |   4 +-
 .../Transforms/NormalizeTransform.cs          |   3 +-
 .../TreeEnsembleFeaturizer.cs                 |   6 +-
 src/Microsoft.ML.Parquet/ParquetLoader.cs     |   5 +-
 .../ColumnTypeInference.cs                    |   4 +-
 src/Microsoft.ML.Transforms/GcnTransform.cs   |   2 +-
 .../KeyToBinaryVectorTransform.cs             |   2 +-
 .../MutualInformationFeatureSelection.cs      |  14 +--
 .../NADropTransform.cs                        |   2 +-
 .../NAIndicatorTransform.cs                   |  42 +++----
 src/Microsoft.ML/Data/TextLoader.cs           |   2 +-
 ...eptron-CV-breast-cancer.PAVcalibration.txt |  32 +++---
 ...ptron-CV-breast-cancer.calibrateRandom.txt |  32 +++---
 ...ceptron-CV-breast-cancer.nocalibration.txt |  32 +++---
 .../AveragedPerceptron-CV-breast-cancer.txt   |  32 +++---
 ...TrainTest-breast-cancer.PAVcalibration.txt |  32 +++---
 ...rainTest-breast-cancer.calibrateRandom.txt |  32 +++---
 ...-TrainTest-breast-cancer.nocalibration.txt |  32 +++---
 ...agedPerceptron-TrainTest-breast-cancer.txt |  32 +++---
 ...earSVM-CV-breast-cancer.PAVcalibration.txt |  32 +++---
 ...nearSVM-CV-breast-cancer.nocalibration.txt |  32 +++---
 ...TrainTest-breast-cancer.PAVcalibration.txt |  32 +++---
 ...-TrainTest-breast-cancer.nocalibration.txt |  32 +++---
 .../LogisticRegression-CV-breast-cancer.txt   |  32 +++---
 ...ression-CV-breast-cancer.withThreshold.txt |  32 +++---
 ...gression-GaussianNorm-CV-breast-cancer.txt |  32 +++---
 ...n-GaussianNorm-TrainTest-breast-cancer.txt |  32 +++---
 ...sticRegression-TrainTest-breast-cancer.txt |  32 +++---
 ...-TrainTest-breast-cancer.withThreshold.txt |  32 +++---
 ...icRegression-bin-norm-CV-breast-cancer.txt |  32 +++---
 ...ssion-bin-norm-TrainTest-breast-cancer.txt |  32 +++---
 ...gression-non-negative-CV-breast-cancer.txt |  32 +++---
 ...n-non-negative-TrainTest-breast-cancer.txt |  32 +++---
 ...gisticRegression-norm-CV-breast-cancer.txt |  32 +++---
 ...egression-norm-TrainTest-breast-cancer.txt |  32 +++---
 .../SDCA/BinarySDCA-CV-breast-cancer.txt      |  32 +++---
 .../SDCA/BinarySDCA-L1-CV-breast-cancer.txt   |  32 +++---
 .../BinarySDCA-L1-TrainTest-breast-cancer.txt |  32 +++---
 ...arySDCA-SmoothedHinge-CV-breast-cancer.txt |  32 +++---
 ...-SmoothedHinge-TrainTest-breast-cancer.txt |  32 +++---
 .../BinarySDCA-TrainTest-breast-cancer.txt    |  32 +++---
 .../SGD/BinarySGD-CV-breast-cancer.txt        |  32 +++---
 .../SGD/BinarySGD-Hinge-CV-breast-cancer.txt  |  32 +++---
 ...inarySGD-Hinge-TrainTest-breast-cancer.txt |  32 +++---
 .../SGD/BinarySGD-TrainTest-breast-cancer.txt |  32 +++---
 .../SymSGD/SymSGD-CV-breast-cancer.txt        |  32 +++---
 .../SymSGD/SymSGD-TrainTest-breast-cancer.txt |  32 +++---
 ...eptron-CV-breast-cancer.PAVcalibration.txt |  32 +++---
 ...ptron-CV-breast-cancer.calibrateRandom.txt |  32 +++---
 ...ceptron-CV-breast-cancer.nocalibration.txt |  32 +++---
 .../AveragedPerceptron-CV-breast-cancer.txt   |  32 +++---
 ...TrainTest-breast-cancer.PAVcalibration.txt |  32 +++---
 ...rainTest-breast-cancer.calibrateRandom.txt |  32 +++---
 ...-TrainTest-breast-cancer.nocalibration.txt |  32 +++---
 ...agedPerceptron-TrainTest-breast-cancer.txt |  32 +++---
 ...earSVM-CV-breast-cancer.PAVcalibration.txt |  32 +++---
 ...nearSVM-CV-breast-cancer.nocalibration.txt |  32 +++---
 ...TrainTest-breast-cancer.PAVcalibration.txt |  32 +++---
 ...-TrainTest-breast-cancer.nocalibration.txt |  32 +++---
 .../LogisticRegression-CV-breast-cancer.txt   |  32 +++---
 ...ression-CV-breast-cancer.withThreshold.txt |  32 +++---
 ...gression-GaussianNorm-CV-breast-cancer.txt |  32 +++---
 ...n-GaussianNorm-TrainTest-breast-cancer.txt |  32 +++---
 ...sticRegression-TrainTest-breast-cancer.txt |  32 +++---
 ...-TrainTest-breast-cancer.withThreshold.txt |  32 +++---
 ...icRegression-bin-norm-CV-breast-cancer.txt |  32 +++---
 ...ssion-bin-norm-TrainTest-breast-cancer.txt |  32 +++---
 ...gression-non-negative-CV-breast-cancer.txt |  32 +++---
 ...n-non-negative-TrainTest-breast-cancer.txt |  32 +++---
 ...gisticRegression-norm-CV-breast-cancer.txt |  32 +++---
 ...egression-norm-TrainTest-breast-cancer.txt |  32 +++---
 .../SDCA/BinarySDCA-CV-breast-cancer.txt      |  32 +++---
 .../SDCA/BinarySDCA-L1-CV-breast-cancer.txt   |  32 +++---
 .../BinarySDCA-L1-TrainTest-breast-cancer.txt |  32 +++---
 ...arySDCA-SmoothedHinge-CV-breast-cancer.txt |  32 +++---
 ...-SmoothedHinge-TrainTest-breast-cancer.txt |  32 +++---
 .../BinarySDCA-TrainTest-breast-cancer.txt    |  32 +++---
 .../SGD/BinarySGD-CV-breast-cancer.txt        |  32 +++---
 .../SGD/BinarySGD-Hinge-CV-breast-cancer.txt  |  32 +++---
 ...inarySGD-Hinge-TrainTest-breast-cancer.txt |  32 +++---
 .../SGD/BinarySGD-TrainTest-breast-cancer.txt |  32 +++---
 .../SymSGD/SymSGD-CV-breast-cancer.txt        |  32 +++---
 .../SymSGD/SymSGD-TrainTest-breast-cancer.txt |  32 +++---
 .../UnitTests/CoreBaseTestClass.cs            |   4 +-
 .../UnitTests/DvTypes.cs                      |  68 -----------
 .../UnitTests/TestCSharpApi.cs                |  10 +-
 .../UnitTests/TestEntryPoints.cs              |   8 +-
 .../TestPredictors.cs                         |  12 +-
 .../DataPipe/TestDataPipeBase.cs              |   4 +-
 .../TestSparseDataView.cs                     |   4 +-
 .../CollectionDataSourceTests.cs              |   9 --
 .../LearningPipelineTests.cs                  |  32 +-----
 test/Microsoft.ML.Tests/OnnxTests.cs          |   2 +-
 .../Scenarios/SentimentPredictionTests.cs     |  22 ++--
 .../SentimentPredictionTests.cs               |   8 +-
 125 files changed, 1357 insertions(+), 1899 deletions(-)

diff --git a/src/Microsoft.ML.Api/ApiUtils.cs b/src/Microsoft.ML.Api/ApiUtils.cs
index 96e821f16e..db360c9b1c 100644
--- a/src/Microsoft.ML.Api/ApiUtils.cs
+++ b/src/Microsoft.ML.Api/ApiUtils.cs
@@ -20,7 +20,7 @@ private static OpCode GetAssignmentOpCode(Type t)
             // REVIEW: This should be a Dictionary<Type, OpCode> based solution.
             // DvTypes, strings, arrays, all nullable types, VBuffers and UInt128.
             if (t == typeof(DvInt8) || t == typeof(DvInt4) || t == typeof(DvInt2) || t == typeof(DvInt1) ||
-                t == typeof(DvBool) || t == typeof(DvText) || t == typeof(string) || t.IsArray ||
+                t == typeof(DvText) || t == typeof(string) || t.IsArray ||
                 (t.IsGenericType && t.GetGenericTypeDefinition() == typeof(VBuffer<>)) ||
                 (t.IsGenericType && t.GetGenericTypeDefinition() == typeof(Nullable<>)) ||
                 t == typeof(DvDateTime) || t == typeof(DvDateTimeZone) || t == typeof(DvTimeSpan) || t == typeof(UInt128))
diff --git a/src/Microsoft.ML.Api/DataViewConstructionUtils.cs b/src/Microsoft.ML.Api/DataViewConstructionUtils.cs
index c50e48e16f..edeee7297f 100644
--- a/src/Microsoft.ML.Api/DataViewConstructionUtils.cs
+++ b/src/Microsoft.ML.Api/DataViewConstructionUtils.cs
@@ -174,12 +174,7 @@ private Delegate CreateGetter(int index)
                         else if (outputType.GetElementType() == typeof(bool))
                         {
                             Ch.Assert(colType.ItemType.IsBool);
-                            return CreateConvertingArrayGetterDelegate<bool, DvBool>(index, x => x);
-                        }
-                        else if (outputType.GetElementType() == typeof(bool?))
-                        {
-                            Ch.Assert(colType.ItemType.IsBool);
-                            return CreateConvertingArrayGetterDelegate<bool?, DvBool>(index, x => x ?? DvBool.NA);
+                            return CreateConvertingArrayGetterDelegate<bool, bool>(index, x => x);
                         }
 
                         // T[] -> VBuffer<T>
@@ -210,15 +205,9 @@ private Delegate CreateGetter(int index)
                         }
                         else if (outputType == typeof(bool))
                         {
-                            // Bool -> DvBool
-                            Ch.Assert(colType.IsBool);
-                            return CreateConvertingGetterDelegate<bool, DvBool>(index, x => x);
-                        }
-                        else if (outputType == typeof(bool?))
-                        {
-                            // Bool? -> DvBool
+                            // Bool -> Bool.
                             Ch.Assert(colType.IsBool);
-                            return CreateConvertingGetterDelegate<bool?, DvBool>(index, x => x ?? DvBool.NA);
+                            return CreateConvertingGetterDelegate<bool, bool>(index, x => x);
                         }
                         else if (outputType == typeof(int))
                         {
diff --git a/src/Microsoft.ML.Api/TypedCursor.cs b/src/Microsoft.ML.Api/TypedCursor.cs
index 19f9a7cf72..8e7e91fe79 100644
--- a/src/Microsoft.ML.Api/TypedCursor.cs
+++ b/src/Microsoft.ML.Api/TypedCursor.cs
@@ -282,12 +282,7 @@ private Action<TRow> GenerateSetter(IRow input, int index, InternalSchemaDefinit
                     else if (fieldType.GetElementType() == typeof(bool))
                     {
                         Ch.Assert(colType.ItemType.IsBool);
-                        return CreateConvertingVBufferSetter<DvBool, bool>(input, index, poke, peek, x => (bool)x);
-                    }
-                    else if (fieldType.GetElementType() == typeof(bool?))
-                    {
-                        Ch.Assert(colType.ItemType.IsBool);
-                        return CreateConvertingVBufferSetter<DvBool, bool?>(input, index, poke, peek, x => (bool?)x);
+                        return CreateConvertingVBufferSetter<bool, bool>(input, index, poke, peek, x => (bool)x);
                     }
                     else if (fieldType.GetElementType() == typeof(int))
                     {
@@ -361,13 +356,7 @@ private Action<TRow> GenerateSetter(IRow input, int index, InternalSchemaDefinit
                     {
                         Ch.Assert(colType.IsBool);
                         Ch.Assert(peek == null);
-                        return CreateConvertingActionSetter<DvBool, bool>(input, index, poke, x => (bool)x);
-                    }
-                    else if (fieldType == typeof(bool?))
-                    {
-                        Ch.Assert(colType.IsBool);
-                        Ch.Assert(peek == null);
-                        return CreateConvertingActionSetter<DvBool, bool?>(input, index, poke, x => (bool?)x);
+                        return CreateConvertingActionSetter<bool, bool>(input, index, poke, x => x);
                     }
                     else if (fieldType == typeof(int))
                     {
diff --git a/src/Microsoft.ML.Core/Data/ColumnType.cs b/src/Microsoft.ML.Core/Data/ColumnType.cs
index 96764d68f1..0581e94ae2 100644
--- a/src/Microsoft.ML.Core/Data/ColumnType.cs
+++ b/src/Microsoft.ML.Core/Data/ColumnType.cs
@@ -573,7 +573,7 @@ public static BoolType Instance
         }
 
         private BoolType()
-            : base(typeof(DvBool), DataKind.BL)
+            : base(typeof(bool), DataKind.BL)
         {
         }
 
diff --git a/src/Microsoft.ML.Core/Data/DataKind.cs b/src/Microsoft.ML.Core/Data/DataKind.cs
index 32325f44a1..27ea6b2e30 100644
--- a/src/Microsoft.ML.Core/Data/DataKind.cs
+++ b/src/Microsoft.ML.Core/Data/DataKind.cs
@@ -163,7 +163,7 @@ public static Type ToType(this DataKind kind)
                 case DataKind.TX:
                     return typeof(DvText);
                 case DataKind.BL:
-                    return typeof(DvBool);
+                    return typeof(bool);
                 case DataKind.TS:
                     return typeof(DvTimeSpan);
                 case DataKind.DT:
@@ -207,7 +207,7 @@ public static bool TryGetDataKind(this Type type, out DataKind kind)
                 kind = DataKind.R8;
             else if (type == typeof(DvText))
                 kind = DataKind.TX;
-            else if (type == typeof(DvBool) || type == typeof(bool) || type == typeof(bool?))
+            else if (type == typeof(bool))
                 kind = DataKind.BL;
             else if (type == typeof(DvTimeSpan))
                 kind = DataKind.TS;
diff --git a/src/Microsoft.ML.Core/Data/DvInt1.cs b/src/Microsoft.ML.Core/Data/DvInt1.cs
index ced2a4688d..6b3e4e3d11 100644
--- a/src/Microsoft.ML.Core/Data/DvInt1.cs
+++ b/src/Microsoft.ML.Core/Data/DvInt1.cs
@@ -7,7 +7,7 @@
 
 namespace Microsoft.ML.Runtime.Data
 {
-    using BL = DvBool;
+    using BL = Boolean;
     using I2 = DvInt2;
     using I4 = DvInt4;
     using I8 = DvInt8;
@@ -93,9 +93,7 @@ public static explicit operator RawIX(IX value)
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         public static explicit operator IX(BL a)
         {
-            if (a.IsNA)
-                return RawNA;
-            return (RawIX)a.RawValue;
+            return Convert.ToSByte(a);
         }
 
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
@@ -200,65 +198,5 @@ public override string ToString()
                 return "NA";
             return _value.ToString();
         }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator ==(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av == bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator !=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av != bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av < bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av <= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av >= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av > bv ? BL.True : BL.False;
-            return BL.NA;
-        }
     }
 }
diff --git a/src/Microsoft.ML.Core/Data/DvInt2.cs b/src/Microsoft.ML.Core/Data/DvInt2.cs
index 33599f6468..74e001e70c 100644
--- a/src/Microsoft.ML.Core/Data/DvInt2.cs
+++ b/src/Microsoft.ML.Core/Data/DvInt2.cs
@@ -7,7 +7,7 @@
 
 namespace Microsoft.ML.Runtime.Data
 {
-    using BL = DvBool;
+    using BL = Boolean;
     using I1 = DvInt1;
     using I4 = DvInt4;
     using I8 = DvInt8;
@@ -93,9 +93,7 @@ public static explicit operator RawIX(IX value)
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         public static explicit operator IX(BL a)
         {
-            if (a.IsNA)
-                return RawNA;
-            return (RawIX)a.RawValue;
+            return Convert.ToInt16(a);
         }
 
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
@@ -199,65 +197,5 @@ public override string ToString()
                 return "NA";
             return _value.ToString();
         }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator ==(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av == bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator !=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av != bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av < bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av <= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av >= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av > bv ? BL.True : BL.False;
-            return BL.NA;
-        }
     }
 }
diff --git a/src/Microsoft.ML.Core/Data/DvInt4.cs b/src/Microsoft.ML.Core/Data/DvInt4.cs
index 23c7e89242..6f67447064 100644
--- a/src/Microsoft.ML.Core/Data/DvInt4.cs
+++ b/src/Microsoft.ML.Core/Data/DvInt4.cs
@@ -7,7 +7,7 @@
 
 namespace Microsoft.ML.Runtime.Data
 {
-    using BL = DvBool;
+    using BL = Boolean;
     using I1 = DvInt1;
     using I2 = DvInt2;
     using I8 = DvInt8;
@@ -93,9 +93,7 @@ public static explicit operator RawIX(IX value)
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         public static explicit operator IX(BL a)
         {
-            if (a.IsNA)
-                return RawNA;
-            return (RawIX)a.RawValue;
+            return Convert.ToInt32(a);
         }
 
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
@@ -199,66 +197,6 @@ public override string ToString()
             return _value.ToString();
         }
 
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator ==(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av == bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator !=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av != bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av < bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av <= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av >= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av > bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         public static IX operator -(IX a)
         {
diff --git a/src/Microsoft.ML.Core/Data/DvInt8.cs b/src/Microsoft.ML.Core/Data/DvInt8.cs
index 3212e21fa6..c172463705 100644
--- a/src/Microsoft.ML.Core/Data/DvInt8.cs
+++ b/src/Microsoft.ML.Core/Data/DvInt8.cs
@@ -7,7 +7,7 @@
 
 namespace Microsoft.ML.Runtime.Data
 {
-    using BL = DvBool;
+    using BL = Boolean;
     using I1 = DvInt1;
     using I2 = DvInt2;
     using I4 = DvInt4;
@@ -92,9 +92,7 @@ public static explicit operator RawIX(IX value)
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         public static explicit operator IX(BL a)
         {
-            if (a.IsNA)
-                return RawNA;
-            return (RawIX)a.RawValue;
+            return Convert.ToInt64(a);
         }
 
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
@@ -201,66 +199,6 @@ public override string ToString()
             return _value.ToString();
         }
 
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator ==(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av == bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator !=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av != bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av < bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator <=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av <= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >=(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av >= bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator >(IX a, IX b)
-        {
-            var av = a._value;
-            var bv = b._value;
-            if (av != RawNA && bv != RawNA)
-                return av > bv ? BL.True : BL.False;
-            return BL.NA;
-        }
-
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         public static IX operator -(IX a)
         {
diff --git a/src/Microsoft.ML.Core/Data/MetadataUtils.cs b/src/Microsoft.ML.Core/Data/MetadataUtils.cs
index 116d521756..ae4ac86469 100644
--- a/src/Microsoft.ML.Core/Data/MetadataUtils.cs
+++ b/src/Microsoft.ML.Core/Data/MetadataUtils.cs
@@ -342,12 +342,12 @@ public static bool HasKeyNames(this ISchema schema, int col, int keyCount)
         /// <param name="schema">The schema to query</param>
         /// <param name="col">Which column in the schema to query</param>
         /// <returns>True if and only if the column has the <see cref="Kinds.IsNormalized"/> metadata
-        /// set to the scalar value <see cref="DvBool.True"/></returns>
+        /// set to the scalar value true</returns>
         public static bool IsNormalized(this ISchema schema, int col)
         {
             Contracts.CheckValue(schema, nameof(schema));
-            var value = default(DvBool);
-            return schema.TryGetMetadata(BoolType.Instance, Kinds.IsNormalized, col, ref value) && value.IsTrue;
+            var value = default(bool);
+            return schema.TryGetMetadata(BoolType.Instance, Kinds.IsNormalized, col, ref value) && value;
         }
 
         /// <summary>
diff --git a/src/Microsoft.ML.Core/Data/TypeUtils.cs b/src/Microsoft.ML.Core/Data/TypeUtils.cs
index 30a9e4008b..b23937d387 100644
--- a/src/Microsoft.ML.Core/Data/TypeUtils.cs
+++ b/src/Microsoft.ML.Core/Data/TypeUtils.cs
@@ -9,8 +9,6 @@ namespace Microsoft.ML.Runtime.Data
 {
     using R4 = Single;
     using R8 = Double;
-    using BL = DvBool;
-    using TX = DvText;
 
     public delegate bool RefPredicate<T>(ref T value);
 
@@ -23,81 +21,5 @@ public static class TypeUtils
         public static bool IsNA(this R4 src) { return R4.IsNaN(src); }
         [MethodImpl(MethodImplOptions.AggressiveInlining)]
         public static bool IsNA(this R8 src) { return R8.IsNaN(src); }
-
-        #region R4
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Eq(this R4 a, R4 b)
-        {
-            return a == b ? BL.True : a.IsNA() || b.IsNA() ? BL.NA : BL.False;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Ne(this R4 a, R4 b)
-        {
-            return a != b ? a.IsNA() || b.IsNA() ? BL.NA : BL.True : BL.False;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Lt(this R4 a, R4 b)
-        {
-            return a < b ? BL.True : a >= b ? BL.False : BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Le(this R4 a, R4 b)
-        {
-            return a <= b ? BL.True : a > b ? BL.False : BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Ge(this R4 a, R4 b)
-        {
-            return a >= b ? BL.True : a < b ? BL.False : BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Gt(this R4 a, R4 b)
-        {
-            return a > b ? BL.True : a <= b ? BL.False : BL.NA;
-        }
-        #endregion R4
-
-        #region R8
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Eq(this R8 a, R8 b)
-        {
-            return a == b ? BL.True : a.IsNA() || b.IsNA() ? BL.NA : BL.False;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Ne(this R8 a, R8 b)
-        {
-            return a != b ? a.IsNA() || b.IsNA() ? BL.NA : BL.True : BL.False;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Lt(this R8 a, R8 b)
-        {
-            return a < b ? BL.True : a >= b ? BL.False : BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Le(this R8 a, R8 b)
-        {
-            return a <= b ? BL.True : a > b ? BL.False : BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Ge(this R8 a, R8 b)
-        {
-            return a >= b ? BL.True : a < b ? BL.False : BL.NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL Gt(this R8 a, R8 b)
-        {
-            return a > b ? BL.True : a <= b ? BL.False : BL.NA;
-        }
-        #endregion R8
     }
 }
diff --git a/src/Microsoft.ML.Data/Commands/TrainCommand.cs b/src/Microsoft.ML.Data/Commands/TrainCommand.cs
index 0cb5bfb4e9..834d0daffc 100644
--- a/src/Microsoft.ML.Data/Commands/TrainCommand.cs
+++ b/src/Microsoft.ML.Data/Commands/TrainCommand.cs
@@ -452,7 +452,6 @@ public static bool AddNormalizerIfNeeded(IHostEnvironment env, IChannel ch, ITra
             {
                 if (autoNorm != NormalizeOption.Yes)
                 {
-                    DvBool isNormalized = DvBool.False;
                     if (!trainer.Info.NeedNormalization || schema.IsNormalized(featCol))
                     {
                         ch.Info("Not adding a normalizer.");
diff --git a/src/Microsoft.ML.Data/Data/Conversion.cs b/src/Microsoft.ML.Data/Data/Conversion.cs
index 0a9833064a..4cc7b0e8f9 100644
--- a/src/Microsoft.ML.Data/Data/Conversion.cs
+++ b/src/Microsoft.ML.Data/Data/Conversion.cs
@@ -11,10 +11,11 @@
 using System.Text;
 using System.Threading;
 using Microsoft.ML.Runtime.Internal.Utilities;
+using System.Runtime.CompilerServices;
 
 namespace Microsoft.ML.Runtime.Data.Conversion
 {
-    using BL = DvBool;
+    using BL = Boolean;
     using DT = DvDateTime;
     using DZ = DvDateTimeZone;
     using I1 = DvInt1;
@@ -250,7 +251,6 @@ private Conversions()
             AddIsNA<I8>(IsNA);
             AddIsNA<R4>(IsNA);
             AddIsNA<R8>(IsNA);
-            AddIsNA<BL>(IsNA);
             AddIsNA<TX>(IsNA);
             AddIsNA<TS>(IsNA);
             AddIsNA<DT>(IsNA);
@@ -262,7 +262,6 @@ private Conversions()
             AddGetNA<I8>(GetNA);
             AddGetNA<R4>(GetNA);
             AddGetNA<R8>(GetNA);
-            AddGetNA<BL>(GetNA);
             AddGetNA<TX>(GetNA);
             AddGetNA<TS>(GetNA);
             AddGetNA<DT>(GetNA);
@@ -274,7 +273,6 @@ private Conversions()
             AddHasNA<I8>(HasNA);
             AddHasNA<R4>(HasNA);
             AddHasNA<R8>(HasNA);
-            AddHasNA<BL>(HasNA);
             AddHasNA<TX>(HasNA);
             AddHasNA<TS>(HasNA);
             AddHasNA<DT>(HasNA);
@@ -852,7 +850,6 @@ public ValueGetter<T> GetNAOrDefaultGetter<T>(ColumnType type)
         private bool IsNA(ref I8 src) => src.IsNA;
         private bool IsNA(ref R4 src) => src.IsNA();
         private bool IsNA(ref R8 src) => src.IsNA();
-        private bool IsNA(ref BL src) => src.IsNA;
         private bool IsNA(ref TS src) => src.IsNA;
         private bool IsNA(ref DT src) => src.IsNA;
         private bool IsNA(ref DZ src) => src.IsNA;
@@ -866,7 +863,6 @@ public ValueGetter<T> GetNAOrDefaultGetter<T>(ColumnType type)
         private bool HasNA(ref VBuffer<I8> src) { for (int i = 0; i < src.Count; i++) { if (src.Values[i].IsNA) return true; } return false; }
         private bool HasNA(ref VBuffer<R4> src) { for (int i = 0; i < src.Count; i++) { if (src.Values[i].IsNA()) return true; } return false; }
         private bool HasNA(ref VBuffer<R8> src) { for (int i = 0; i < src.Count; i++) { if (src.Values[i].IsNA()) return true; } return false; }
-        private bool HasNA(ref VBuffer<BL> src) { for (int i = 0; i < src.Count; i++) { if (src.Values[i].IsNA) return true; } return false; }
         private bool HasNA(ref VBuffer<TS> src) { for (int i = 0; i < src.Count; i++) { if (src.Values[i].IsNA) return true; } return false; }
         private bool HasNA(ref VBuffer<DT> src) { for (int i = 0; i < src.Count; i++) { if (src.Values[i].IsNA) return true; } return false; }
         private bool HasNA(ref VBuffer<DZ> src) { for (int i = 0; i < src.Count; i++) { if (src.Values[i].IsNA) return true; } return false; }
@@ -881,7 +877,7 @@ public ValueGetter<T> GetNAOrDefaultGetter<T>(ColumnType type)
         private bool IsDefault(ref R4 src) => src == 0;
         private bool IsDefault(ref R8 src) => src == 0;
         private bool IsDefault(ref TX src) => src.IsEmpty;
-        private bool IsDefault(ref BL src) => src.IsFalse;
+        private bool IsDefault(ref BL src) => !src;
         private bool IsDefault(ref U1 src) => src == 0;
         private bool IsDefault(ref U2 src) => src == 0;
         private bool IsDefault(ref U4 src) => src == 0;
@@ -906,7 +902,6 @@ public ValueGetter<T> GetNAOrDefaultGetter<T>(ColumnType type)
         private void GetNA(ref I8 value) => value = I8.NA;
         private void GetNA(ref R4 value) => value = R4.NaN;
         private void GetNA(ref R8 value) => value = R8.NaN;
-        private void GetNA(ref BL value) => value = BL.NA;
         private void GetNA(ref TS value) => value = TS.NA;
         private void GetNA(ref DT value) => value = DT.NA;
         private void GetNA(ref DZ value) => value = DZ.NA;
@@ -1036,9 +1031,9 @@ public ValueGetter<T> GetNAOrDefaultGetter<T>(ColumnType type)
         public void Convert(ref BL src, ref SB dst)
         {
             ClearDst(ref dst);
-            if (src.IsFalse)
+            if (!src)
                 dst.Append("0");
-            else if (src.IsTrue)
+            else if (src)
                 dst.Append("1");
         }
         public void Convert(ref TS src, ref SB dst) { ClearDst(ref dst); if (!src.IsNA) dst.AppendFormat("{0:c}", (TimeSpan)src); }
@@ -1621,7 +1616,7 @@ public bool TryParse(ref TX src, out BL dst)
             // NA text fails.
             if (src.IsNA)
             {
-                dst = BL.NA;
+                dst = false;
                 return true;
             }
 
@@ -1630,7 +1625,7 @@ public bool TryParse(ref TX src, out BL dst)
             {
             case 0:
                 // Empty succeeds and maps to false.
-                dst = BL.False;
+                dst = false;
                 return true;
 
             case 1:
@@ -1642,7 +1637,7 @@ public bool TryParse(ref TX src, out BL dst)
                 case 'y':
                 case '1':
                 case '+':
-                    dst = BL.True;
+                    dst = true;
                     return true;
                 case 'F':
                 case 'f':
@@ -1650,7 +1645,7 @@ public bool TryParse(ref TX src, out BL dst)
                 case 'n':
                 case '0':
                 case '-':
-                    dst = BL.False;
+                    dst = false;
                     return true;
                 }
                 break;
@@ -1662,17 +1657,17 @@ public bool TryParse(ref TX src, out BL dst)
                 case 'n':
                     if ((ch = src[1]) != 'O' && ch != 'o')
                         break;
-                    dst = BL.False;
+                    dst = false;
                     return true;
                 case '+':
                     if ((ch = src[1]) != '1')
                         break;
-                    dst = BL.True;
+                    dst = true;
                     return true;
                 case '-':
                     if ((ch = src[1]) != '1')
                         break;
-                    dst = BL.False;
+                    dst = false;
                     return true;
                 }
                 break;
@@ -1686,7 +1681,7 @@ public bool TryParse(ref TX src, out BL dst)
                         break;
                     if ((ch = src[2]) != 'S' && ch != 's')
                         break;
-                    dst = BL.True;
+                    dst = true;
                     return true;
                 }
                 break;
@@ -1702,7 +1697,7 @@ public bool TryParse(ref TX src, out BL dst)
                         break;
                     if ((ch = src[3]) != 'E' && ch != 'e')
                         break;
-                    dst = BL.True;
+                    dst = true;
                     return true;
                 }
                 break;
@@ -1720,13 +1715,13 @@ public bool TryParse(ref TX src, out BL dst)
                         break;
                     if ((ch = src[4]) != 'E' && ch != 'e')
                         break;
-                    dst = BL.False;
+                    dst = false;
                     return true;
                 }
                 break;
             }
 
-            dst = BL.NA;
+            dst = false;
             return IsStdMissing(ref src);
         }
 
@@ -1793,9 +1788,9 @@ public void Convert(ref TX span, ref TX value)
         }
         public void Convert(ref TX span, ref BL value)
         {
-            // When TryParseBL returns false, it should have set value to NA.
+            // When TryParseBL returns false, it should have set value to false.
             if (!TryParse(ref span, out value))
-                Contracts.Assert(value.IsNA);
+                Contracts.Assert(!value);
         }
         public void Convert(ref TX src, ref SB dst)
         {
@@ -1826,8 +1821,8 @@ public void Convert(ref TX span, ref DZ value)
         public void Convert(ref BL src, ref I2 dst) => dst = (I2)src;
         public void Convert(ref BL src, ref I4 dst) => dst = (I4)src;
         public void Convert(ref BL src, ref I8 dst) => dst = (I8)src;
-        public void Convert(ref BL src, ref R4 dst) => dst = (R4)src;
-        public void Convert(ref BL src, ref R8 dst) => dst = (R8)src;
+        public void Convert(ref BL src, ref R4 dst) => dst = System.Convert.ToSingle(src);
+        public void Convert(ref BL src, ref R8 dst) => dst = System.Convert.ToDouble(src);
         public void Convert(ref BL src, ref BL dst) => dst = src;
         #endregion FromBL
     }
diff --git a/src/Microsoft.ML.Data/Data/RowCursorUtils.cs b/src/Microsoft.ML.Data/Data/RowCursorUtils.cs
index 091fe26cb2..9f09e0da51 100644
--- a/src/Microsoft.ML.Data/Data/RowCursorUtils.cs
+++ b/src/Microsoft.ML.Data/Data/RowCursorUtils.cs
@@ -394,16 +394,16 @@ private static ValueGetter<Single> GetLabelGetterNotFloat(IRow cursor, int label
 
             Contracts.Assert(type != NumberType.R4 && type != NumberType.R8);
 
-            // DvBool type label mapping: True -> 1, False -> 0, NA -> NaN.
+            // boolean type label mapping: True -> 1, False -> 0.
             if (type.IsBool)
             {
-                var getBoolSrc = cursor.GetGetter<DvBool>(labelIndex);
+                var getBoolSrc = cursor.GetGetter<bool>(labelIndex);
                 return
                     (ref Single dst) =>
                     {
-                        DvBool src = DvBool.NA;
+                        bool src = default;
                         getBoolSrc(ref src);
-                        dst = (Single)src;
+                        dst = Convert.ToSingle(src);
                     };
             }
 
diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
index d04adaf099..df0d57f3c6 100644
--- a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
+++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
@@ -61,10 +61,6 @@ public CodecFactory(IHostEnvironment env, MemoryStreamPool memPool = null)
             RegisterSimpleCodec(new DateTimeZoneCodec(this));
             RegisterSimpleCodec(new UnsafeTypeCodec<UInt128>(this));
 
-            // Register the old boolean reading codec.
-            var oldBool = new OldBoolCodec(this);
-            RegisterOtherCodec(oldBool.LoadName, oldBool.GetCodec);
-
             RegisterOtherCodec("VBuffer", GetVBufferCodec);
             RegisterOtherCodec("Key", GetKeyCodec);
         }
diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
index f840773872..f2ec97ac12 100644
--- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
+++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
@@ -420,90 +420,27 @@ public override void Get(ref DvText value)
             }
         }
 
-        /// <summary>
-        /// This is an older boolean code that reads from a form that serialized
-        /// 1 bit per value. The new encoding (implemented by a different codec)
-        /// uses 2 bits per value so NA values can be supported.
-        /// </summary>
-        private sealed class OldBoolCodec : SimpleCodec<DvBool>
+        private sealed class BoolCodec : SimpleCodec<bool>
         {
             // *** Binary block format ***
-            // Packed bits.
-
-            public OldBoolCodec(CodecFactory factory)
-                : base(factory, BoolType.Instance)
-            {
-            }
-
-            public override string LoadName
-            {
-                get { return typeof(bool).Name; }
-            }
-
-            public override IValueWriter<DvBool> OpenWriter(Stream stream)
-            {
-                Contracts.Assert(false, "This older form only supports reading");
-                throw Contracts.ExceptNotSupp("Writing single bit booleans no longer supported");
-            }
-
-            public override IValueReader<DvBool> OpenReader(Stream stream, int items)
-            {
-                return new Reader(this, stream, items);
-            }
-
-            private sealed class Reader : ValueReaderBase<DvBool>
-            {
-                private byte _currentBits;
-                private int _currentIndex;
-                private int _remaining;
-
-                public Reader(OldBoolCodec codec, Stream stream, int items)
-                    : base(codec.Factory, stream)
-                {
-                    _remaining = items;
-                    _currentIndex = -1;
-                }
-
-                public override void MoveNext()
-                {
-                    Contracts.Assert(0 < _remaining, "already consumed all values");
-                    --_remaining;
-                    if ((_currentIndex = (_currentIndex + 1) & 7) == 0)
-                        _currentBits = Reader.ReadByte();
-                    else
-                        _currentBits >>= 1;
-                }
-
-                public override void Get(ref DvBool value)
-                {
-                    Contracts.Assert(0 <= _currentIndex, "have not moved in");
-                    Contracts.Assert(_currentIndex < 8);
-                    value = (_currentBits & 1) != 0;
-                }
-            }
-        }
-
-        private sealed class BoolCodec : SimpleCodec<DvBool>
-        {
-            // *** Binary block format ***
-            // Pack 16 values into 32 bits, with 00 for false, 01 for true and 10 for NA.
+            // Pack 32 values into 32 bits, with 0 for false, 1 for true.
 
             public BoolCodec(CodecFactory factory)
                 : base(factory, BoolType.Instance)
             {
             }
 
-            public override IValueWriter<DvBool> OpenWriter(Stream stream)
+            public override IValueWriter<bool> OpenWriter(Stream stream)
             {
                 return new Writer(this, stream);
             }
 
-            public override IValueReader<DvBool> OpenReader(Stream stream, int items)
+            public override IValueReader<bool> OpenReader(Stream stream, int items)
             {
                 return new Reader(this, stream, items);
             }
 
-            private sealed class Writer : ValueWriterBase<DvBool>
+            private sealed class Writer : ValueWriterBase<bool>
             {
                 // Pack 16 values into 32 bits.
                 private int _currentBits;
@@ -515,18 +452,15 @@ public Writer(BoolCodec codec, Stream stream)
                 {
                 }
 
-                public override void Write(ref DvBool value)
+                public override void Write(ref bool value)
                 {
                     Contracts.Assert(0 <= _currentIndex && _currentIndex < 32);
-                    Contracts.Assert((_currentIndex & 1) == 0);
 
                     _numWritten++;
-                    if (value.IsTrue)
+                    if (value)
                         _currentBits |= 1 << _currentIndex;
-                    else if (!value.IsFalse)
-                        _currentBits |= 2 << _currentIndex;
 
-                    _currentIndex += 2;
+                    _currentIndex++;
                     if (_currentIndex == 32)
                     {
                         Writer.Write(_currentBits);
@@ -553,7 +487,7 @@ public override void Commit()
                 }
             }
 
-            private sealed class Reader : ValueReaderBase<DvBool>
+            private sealed class Reader : ValueReaderBase<bool>
             {
                 private int _currentBits;
                 private int _currentSlot;
@@ -570,30 +504,17 @@ public override void MoveNext()
                 {
                     Contracts.Assert(0 < _remaining, "already consumed all values");
                     --_remaining;
-                    if ((_currentSlot = (_currentSlot + 1) & 0x0F) == 0)
+                    if ((_currentSlot = (_currentSlot + 1) & 0x1F) == 0)
                         _currentBits = Reader.ReadInt32();
                     else
-                        _currentBits = (int)((uint)_currentBits >> 2);
+                        _currentBits = (int)((uint)_currentBits >> 1);
                 }
 
-                public override void Get(ref DvBool value)
+                public override void Get(ref bool value)
                 {
                     Contracts.Assert(0 <= _currentSlot, "have not moved in");
-                    Contracts.Assert(_currentSlot < 16);
-                    switch (_currentBits & 0x3)
-                    {
-                    case 0x0:
-                        value = DvBool.False;
-                        break;
-                    case 0x1:
-                        value = DvBool.True;
-                        break;
-                    case 0x2:
-                        value = DvBool.NA;
-                        break;
-                    default:
-                        throw Contracts.ExceptDecode("Invalid bit pattern in BoolCodec");
-                    }
+                    Contracts.Assert(_currentSlot < 32);
+                    value = Convert.ToBoolean(_currentBits & 0x1);
                 }
             }
         }
diff --git a/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs
index 71c08eecd0..305dfe8478 100644
--- a/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs
+++ b/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs
@@ -218,7 +218,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
         {
             var stratCol = new List<uint>();
             var stratVal = new List<DvText>();
-            var isWeighted = new List<DvBool>();
+            var isWeighted = new List<bool>();
             var auc = new List<Double>();
             var accuracy = new List<Double>();
             var posPrec = new List<Double>();
@@ -259,7 +259,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
                     agg.Finish();
                     stratCol.Add(stratColKey);
                     stratVal.Add(stratColVal);
-                    isWeighted.Add(DvBool.False);
+                    isWeighted.Add(false);
                     auc.Add(agg.UnweightedAuc);
                     accuracy.Add(agg.UnweightedCounters.Acc);
                     posPrec.Add(agg.UnweightedCounters.PrecisionPos);
@@ -298,7 +298,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
                     {
                         stratCol.Add(stratColKey);
                         stratVal.Add(stratColVal);
-                        isWeighted.Add(DvBool.True);
+                        isWeighted.Add(true);
                         auc.Add(agg.WeightedAuc);
                         accuracy.Add(agg.WeightedCounters.Acc);
                         posPrec.Add(agg.WeightedCounters.PrecisionPos);
@@ -931,7 +931,7 @@ public override Delegate[] CreateGetters(IRow input, Func<int, bool> activeCols,
                 scoreGetter = nanGetter;
 
             Action updateCacheIfNeeded;
-            Func<DvBool> getPredictedLabel;
+            Func<bool> getPredictedLabel;
             if (_useRaw)
             {
                 updateCacheIfNeeded =
@@ -965,8 +965,8 @@ public override Delegate[] CreateGetters(IRow input, Func<int, bool> activeCols,
             var getters = _probIndex >= 0 ? new Delegate[2] : new Delegate[1];
             if (activeCols(AssignedCol))
             {
-                ValueGetter<DvBool> predFn =
-                    (ref DvBool dst) =>
+                ValueGetter<bool> predFn =
+                    (ref bool dst) =>
                     {
                         updateCacheIfNeeded();
                         dst = getPredictedLabel();
@@ -995,9 +995,10 @@ private Double GetLogLoss(Single prob, Single label)
             return -Math.Log(1.0 - prob, 2);
         }
 
-        private DvBool GetPredictedLabel(Single val)
+        private bool GetPredictedLabel(Single val)
         {
-            return val.IsNA() ? DvBool.NA : val > _threshold ? DvBool.True : DvBool.False;
+            //Behavior for NA values is undefined.
+            return val.IsNA() ? false : val > _threshold ? true : false;
         }
 
         public override RowMapperColumnInfo[] GetOutputColumns()
diff --git a/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs
index bec1ac144a..5100ffd0e9 100644
--- a/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs
+++ b/src/Microsoft.ML.Data/Evaluators/ClusteringEvaluator.cs
@@ -119,7 +119,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
         {
             var stratCol = new List<uint>();
             var stratVal = new List<DvText>();
-            var isWeighted = new List<DvBool>();
+            var isWeighted = new List<bool>();
             var nmi = new List<Double>();
             var avgMinScores = new List<Double>();
             var dbi = new List<Double>();
@@ -136,7 +136,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
 
                     stratCol.Add(stratColKey);
                     stratVal.Add(stratColVal);
-                    isWeighted.Add(DvBool.False);
+                    isWeighted.Add(false);
                     nmi.Add(agg.UnweightedCounters.Nmi);
                     avgMinScores.Add(agg.UnweightedCounters.AvgMinScores);
                     if (agg.UnweightedCounters.CalculateDbi)
@@ -145,7 +145,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
                     {
                         stratCol.Add(stratColKey);
                         stratVal.Add(stratColVal);
-                        isWeighted.Add(DvBool.True);
+                        isWeighted.Add(true);
                         nmi.Add(agg.WeightedCounters.Nmi);
                         avgMinScores.Add(agg.WeightedCounters.AvgMinScores);
                         if (agg.WeightedCounters.CalculateDbi)
diff --git a/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs b/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs
index 942d139425..3bf076fa7b 100644
--- a/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs
+++ b/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs
@@ -272,12 +272,12 @@ public static IEnumerable<KeyValuePair<string, double>> GetMetrics(IDataView met
 
             using (var cursor = metricsView.GetRowCursor(col => true))
             {
-                DvBool isWeighted = DvBool.False;
-                ValueGetter<DvBool> isWeightedGetter;
+                bool isWeighted = false;
+                ValueGetter<bool> isWeightedGetter;
                 if (hasWeighted)
-                    isWeightedGetter = cursor.GetGetter<DvBool>(isWeightedCol);
+                    isWeightedGetter = cursor.GetGetter<bool>(isWeightedCol);
                 else
-                    isWeightedGetter = (ref DvBool dst) => dst = DvBool.False;
+                    isWeightedGetter = (ref bool dst) => dst = false;
 
                 ValueGetter<uint> stratColGetter;
                 if (hasStrats)
@@ -313,7 +313,7 @@ public static IEnumerable<KeyValuePair<string, double>> GetMetrics(IDataView met
                 while (cursor.MoveNext())
                 {
                     isWeightedGetter(ref isWeighted);
-                    if (isWeighted.IsTrue)
+                    if (isWeighted)
                         continue;
 
                     stratColGetter(ref strat);
@@ -1098,12 +1098,12 @@ internal static AggregatedMetric[] ComputeMetricsSum(IHostEnvironment env, IData
             AggregatedMetric[] agg;
             using (var cursor = data.GetRowCursor(col => true))
             {
-                DvBool isWeighted = DvBool.False;
-                ValueGetter<DvBool> isWeightedGetter;
+                bool isWeighted = false;
+                ValueGetter<bool> isWeightedGetter;
                 if (hasWeighted)
-                    isWeightedGetter = cursor.GetGetter<DvBool>(isWeightedCol);
+                    isWeightedGetter = cursor.GetGetter<bool>(isWeightedCol);
                 else
-                    isWeightedGetter = (ref DvBool dst) => dst = DvBool.False;
+                    isWeightedGetter = (ref bool dst) => dst = false;
 
                 ValueGetter<uint> stratColGetter;
                 if (hasStrats)
@@ -1141,7 +1141,7 @@ internal static AggregatedMetric[] ComputeMetricsSum(IHostEnvironment env, IData
                         continue;
 
                     isWeightedGetter(ref isWeighted);
-                    if (isWeighted.IsTrue)
+                    if (isWeighted)
                     {
                         // If !average, we should have only one relevant row.
                         if (numWeightedResults > numFolds)
@@ -1256,8 +1256,8 @@ internal static IDataView GetAverageToDataView(IHostEnvironment env, ISchema sch
                 else if (i == isWeightedCol)
                 {
                     env.AssertValue(weightedDvBldr);
-                    dvBldr.AddColumn(MetricKinds.ColumnNames.IsWeighted, BoolType.Instance, foldCol >= 0 ? new[] { DvBool.False, DvBool.False } : new[] { DvBool.False });
-                    weightedDvBldr.AddColumn(MetricKinds.ColumnNames.IsWeighted, BoolType.Instance, foldCol >= 0 ? new[] { DvBool.True, DvBool.True } : new[] { DvBool.True });
+                    dvBldr.AddColumn(MetricKinds.ColumnNames.IsWeighted, BoolType.Instance, foldCol >= 0 ? new[] { false, true} : new[] { false });
+                    weightedDvBldr.AddColumn(MetricKinds.ColumnNames.IsWeighted, BoolType.Instance, foldCol >= 0 ? new[] { true, true } : new[] { true });
                 }
                 else if (i == foldCol)
                 {
@@ -1480,7 +1480,7 @@ private static double[][] GetConfusionTableAsArray(IDataView confusionDataView,
         /// stratified metrics, it must contain two text columns named "StratCol" and "StratVal", containing the stratification column
         /// name, and a text description of the value. In this case, the value of column StratVal in the row corresponding to the entire
         /// dataset should contain the text "overall", and the value of column StratCol should be DvText.NA. If weighted metrics are present
-        /// then the data view should also contain a DvBool column named "IsWeighted".</param>
+        /// then the data view should also contain a bool column named "IsWeighted".</param>
         /// <param name="weightedMetrics">If the IsWeighted column exists, this is assigned the string representation of the weighted
         /// metrics. Otherwise it is assigned null.</param>
         public static string GetPerFoldResults(IHostEnvironment env, IDataView fold, out string weightedMetrics)
@@ -1510,7 +1510,7 @@ private static string GetOverallMetricsAsString(double[] sumMetrics, double[] su
 
         // This method returns a string representation of a set of metrics. If there are stratification columns, it looks for columns named
         // StratCol and StratVal, and outputs the metrics in the rows with NA in the StratCol column. If weighted is true, it looks
-        // for a DvBool column named "IsWeighted" and outputs the metrics in the rows with a value of true in that column.
+        // for a bool column named "IsWeighted" and outputs the metrics in the rows with a value of true in that column.
         // If nonAveragedCols is non-null, it computes the average and standard deviation over all the relevant rows and populates
         // nonAveragedCols with columns that are either hidden, or are not of a type that we can display (i.e., either a numeric column,
         // or a known length vector of doubles).
diff --git a/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs
index d57835b168..be24b908a3 100644
--- a/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs
+++ b/src/Microsoft.ML.Data/Evaluators/MultiOutputRegressionEvaluator.cs
@@ -98,7 +98,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
         {
             var stratCol = new List<uint>();
             var stratVal = new List<DvText>();
-            var isWeighted = new List<DvBool>();
+            var isWeighted = new List<bool>();
             var l1 = new List<Double>();
             var l2 = new List<Double>();
             var dist = new List<Double>();
@@ -117,7 +117,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
 
                     stratCol.Add(stratColKey);
                     stratVal.Add(stratColVal);
-                    isWeighted.Add(DvBool.False);
+                    isWeighted.Add(false);
                     l1.Add(agg.UnweightedCounters.L1);
                     l2.Add(agg.UnweightedCounters.L2);
                     dist.Add(agg.UnweightedCounters.Dist);
@@ -129,7 +129,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
                     {
                         stratCol.Add(stratColKey);
                         stratVal.Add(stratColVal);
-                        isWeighted.Add(DvBool.True);
+                        isWeighted.Add(true);
                         l1.Add(agg.WeightedCounters.L1);
                         l2.Add(agg.WeightedCounters.L2);
                         dist.Add(agg.WeightedCounters.Dist);
@@ -680,12 +680,12 @@ protected override void PrintFoldResultsCore(IChannel ch, Dictionary<string, IDa
 
             using (var cursor = fold.GetRowCursor(col => true))
             {
-                DvBool isWeighted = DvBool.False;
-                ValueGetter<DvBool> isWeightedGetter;
+                bool isWeighted = false;
+                ValueGetter<bool> isWeightedGetter;
                 if (needWeighted)
-                    isWeightedGetter = cursor.GetGetter<DvBool>(isWeightedCol);
+                    isWeightedGetter = cursor.GetGetter<bool>(isWeightedCol);
                 else
-                    isWeightedGetter = (ref DvBool dst) => dst = DvBool.False;
+                    isWeightedGetter = (ref bool dst) => dst = false;
 
                 ValueGetter<uint> stratGetter;
                 if (hasStrats)
@@ -733,12 +733,12 @@ protected override void PrintFoldResultsCore(IChannel ch, Dictionary<string, IDa
                 while (cursor.MoveNext())
                 {
                     isWeightedGetter(ref isWeighted);
-                    if (foundWeighted && isWeighted.IsTrue || foundUnweighted && isWeighted.IsFalse)
+                    if (foundWeighted && isWeighted || foundUnweighted && !isWeighted)
                     {
                         throw ch.Except("Multiple {0} rows found in overall metrics data view",
-                            isWeighted.IsTrue ? "weighted" : "unweighted");
+                            isWeighted ? "weighted" : "unweighted");
                     }
-                    if (isWeighted.IsTrue)
+                    if (isWeighted)
                         foundWeighted = true;
                     else
                         foundUnweighted = true;
@@ -754,7 +754,7 @@ protected override void PrintFoldResultsCore(IChannel ch, Dictionary<string, IDa
                             vBufferGetters[i](ref metricVals);
                             ch.Assert(metricVals.Length == labelCount);
 
-                            sb.AppendFormat("{0}{1,12}:", isWeighted.IsTrue ? "Weighted " : "", fold.Schema.GetColumnName(i));
+                            sb.AppendFormat("{0}{1,12}:", isWeighted ? "Weighted " : "", fold.Schema.GetColumnName(i));
                             foreach (var metric in metricVals.Items(all: true))
                                 sb.AppendFormat(" {0,20:G20}", metric.Value);
                             sb.AppendLine();
diff --git a/src/Microsoft.ML.Data/Evaluators/MulticlassClassifierEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/MulticlassClassifierEvaluator.cs
index fd23e7c3b0..fa919ef16d 100644
--- a/src/Microsoft.ML.Data/Evaluators/MulticlassClassifierEvaluator.cs
+++ b/src/Microsoft.ML.Data/Evaluators/MulticlassClassifierEvaluator.cs
@@ -139,7 +139,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
         {
             var stratCol = new List<uint>();
             var stratVal = new List<DvText>();
-            var isWeighted = new List<DvBool>();
+            var isWeighted = new List<bool>();
 
             var microAcc = new List<Double>();
             var macroAcc = new List<Double>();
@@ -165,7 +165,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
 
                     stratCol.Add(stratColKey);
                     stratVal.Add(stratColVal);
-                    isWeighted.Add(DvBool.False);
+                    isWeighted.Add(false);
                     microAcc.Add(agg.UnweightedCounters.MicroAvgAccuracy);
                     macroAcc.Add(agg.UnweightedCounters.MacroAvgAccuracy);
                     logLoss.Add(agg.UnweightedCounters.LogLoss);
@@ -182,7 +182,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
                     {
                         stratCol.Add(stratColKey);
                         stratVal.Add(stratColVal);
-                        isWeighted.Add(DvBool.True);
+                        isWeighted.Add(true);
                         microAcc.Add(agg.WeightedCounters.MicroAvgAccuracy);
                         macroAcc.Add(agg.WeightedCounters.MacroAvgAccuracy);
                         logLoss.Add(agg.WeightedCounters.LogLoss);
diff --git a/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs
index 616cff8394..d3a0a854b5 100644
--- a/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs
+++ b/src/Microsoft.ML.Data/Evaluators/RankerEvaluator.cs
@@ -151,7 +151,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
         {
             var stratCol = new List<uint>();
             var stratVal = new List<DvText>();
-            var isWeighted = new List<DvBool>();
+            var isWeighted = new List<bool>();
             var ndcg = new List<Double[]>();
             var dcg = new List<Double[]>();
 
@@ -175,7 +175,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
 
                     stratCol.Add(stratColKey);
                     stratVal.Add(stratColVal);
-                    isWeighted.Add(DvBool.False);
+                    isWeighted.Add(false);
                     ndcg.Add(agg.UnweightedCounters.Ndcg);
                     dcg.Add(agg.UnweightedCounters.Dcg);
                     if (agg.UnweightedCounters.GroupSummary)
@@ -192,7 +192,7 @@ protected override void GetAggregatorConsolidationFuncs(Aggregator aggregator, A
                     {
                         stratCol.Add(stratColKey);
                         stratVal.Add(stratColVal);
-                        isWeighted.Add(DvBool.True);
+                        isWeighted.Add(true);
                         ndcg.Add(agg.WeightedCounters.Ndcg);
                         dcg.Add(agg.WeightedCounters.Dcg);
                     }
diff --git a/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs b/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs
index 9962897373..c4ee642a61 100644
--- a/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs
+++ b/src/Microsoft.ML.Data/Evaluators/RegressionEvaluatorBase.cs
@@ -47,7 +47,7 @@ protected override void GetAggregatorConsolidationFuncs(TAgg aggregator, Aggrega
         {
             var stratCol = new List<uint>();
             var stratVal = new List<DvText>();
-            var isWeighted = new List<DvBool>();
+            var isWeighted = new List<bool>();
             var l1 = new List<TMetrics>();
             var l2 = new List<TMetrics>();
             var rms = new List<TMetrics>();
@@ -64,7 +64,7 @@ protected override void GetAggregatorConsolidationFuncs(TAgg aggregator, Aggrega
 
                     stratCol.Add(stratColKey);
                     stratVal.Add(stratColVal);
-                    isWeighted.Add(DvBool.False);
+                    isWeighted.Add(false);
                     l1.Add(agg.UnweightedCounters.L1);
                     l2.Add(agg.UnweightedCounters.L2);
                     rms.Add(agg.UnweightedCounters.Rms);
@@ -74,7 +74,7 @@ protected override void GetAggregatorConsolidationFuncs(TAgg aggregator, Aggrega
                     {
                         stratCol.Add(stratColKey);
                         stratVal.Add(stratColVal);
-                        isWeighted.Add(DvBool.True);
+                        isWeighted.Add(true);
                         l1.Add(agg.WeightedCounters.L1);
                         l2.Add(agg.WeightedCounters.L2);
                         rms.Add(agg.WeightedCounters.Rms);
diff --git a/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs b/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs
index 6da402431d..bf454a0f85 100644
--- a/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs
+++ b/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs
@@ -250,8 +250,8 @@ protected override Delegate GetPredictedLabelGetter(IRow output, out Delegate sc
                 return predFnAsKey;
             }
 
-            ValueGetter<DvBool> predFn =
-                (ref DvBool dst) =>
+            ValueGetter<bool> predFn =
+                (ref bool dst) =>
                 {
                     EnsureCachedPosition(ref cachedPosition, ref score, output, mapperScoreGetter);
                     GetPredictedLabelCore(score, ref dst);
@@ -259,9 +259,10 @@ protected override Delegate GetPredictedLabelGetter(IRow output, out Delegate sc
             return predFn;
         }
 
-        private void GetPredictedLabelCore(Float score, ref DvBool value)
+        private void GetPredictedLabelCore(Float score, ref bool value)
         {
-            value = score > _threshold ? DvBool.True : score <= _threshold ? DvBool.False : DvBool.NA;
+            //Behavior for NA values is undefined.
+            value = score > _threshold ? true : false;
         }
 
         private void GetPredictedLabelCoreAsKey(Float score, ref uint value)
diff --git a/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs b/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs
index 0f115bb2f0..dac61b136a 100644
--- a/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs
+++ b/src/Microsoft.ML.Data/Scorers/ScoreMapperSchema.cs
@@ -205,14 +205,14 @@ public override void GetMetadata<TValue>(string kind, int col, ref TValue value)
             Contracts.CheckParam(0 <= col && col < ColumnCount, nameof(col));
 
             if (col == base.ColumnCount && kind == MetadataUtils.Kinds.IsNormalized)
-                MetadataUtils.Marshal<DvBool, TValue>(IsNormalized, col, ref value);
+                MetadataUtils.Marshal<bool, TValue>(IsNormalized, col, ref value);
             else
                 base.GetMetadata<TValue>(kind, col, ref value);
         }
 
-        private void IsNormalized(int col, ref DvBool dst)
+        private void IsNormalized(int col, ref bool dst)
         {
-            dst = DvBool.True;
+            dst = true;
         }
 
         protected override void GetScoreValueKind(int col, ref DvText dst)
diff --git a/src/Microsoft.ML.Data/Transforms/ConcatTransform.cs b/src/Microsoft.ML.Data/Transforms/ConcatTransform.cs
index b2024cc18c..30671e0fb3 100644
--- a/src/Microsoft.ML.Data/Transforms/ConcatTransform.cs
+++ b/src/Microsoft.ML.Data/Transforms/ConcatTransform.cs
@@ -409,7 +409,7 @@ protected override void GetMetadataCore<TValue>(string kind, int iinfo, ref TVal
                     case MetadataUtils.Kinds.IsNormalized:
                         if (!_isNormalized[iinfo])
                             throw MetadataUtils.ExceptGetMetadata();
-                        MetadataUtils.Marshal<DvBool, TValue>(IsNormalized, iinfo, ref value);
+                        MetadataUtils.Marshal<bool, TValue>(IsNormalized, iinfo, ref value);
                         break;
                     default:
                         base.GetMetadataCore(kind, iinfo, ref value);
@@ -443,9 +443,9 @@ private void GetCategoricalSlotRanges(int iiinfo, ref VBuffer<DvInt4> dst)
                 dst = new VBuffer<DvInt4>(allValues.Count, allValues.ToArray());
             }
 
-            private void IsNormalized(int iinfo, ref DvBool dst)
+            private void IsNormalized(int iinfo, ref bool dst)
             {
-                dst = DvBool.True;
+                dst = true;
             }
 
             private void GetSlotNames(int iinfo, ref VBuffer<DvText> dst)
diff --git a/src/Microsoft.ML.Data/Transforms/ConvertTransform.cs b/src/Microsoft.ML.Data/Transforms/ConvertTransform.cs
index 52005c7558..eec59c8a8f 100644
--- a/src/Microsoft.ML.Data/Transforms/ConvertTransform.cs
+++ b/src/Microsoft.ML.Data/Transforms/ConvertTransform.cs
@@ -246,7 +246,7 @@ private void SetMetadata()
                 using (var bldr = md.BuildMetadata(iinfo, Source.Schema, info.Source, PassThrough))
                 {
                     if (info.TypeSrc.IsBool && _exes[iinfo].TypeDst.ItemType.IsNumber)
-                        bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, DvBool.True);
+                        bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, true);
                 }
             }
             md.Seal();
diff --git a/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs b/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs
index cacd681141..05143f8aa9 100644
--- a/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs
+++ b/src/Microsoft.ML.Data/Transforms/GenerateNumberTransform.cs
@@ -213,17 +213,17 @@ protected override void GetMetadataCore<TValue>(string kind, int iinfo, ref TVal
                 Contracts.Assert(0 <= iinfo & iinfo < InfoCount);
                 if (kind == MetadataUtils.Kinds.IsNormalized && !UseCounter[iinfo])
                 {
-                    MetadataUtils.Marshal<DvBool, TValue>(IsNormalized, iinfo, ref value);
+                    MetadataUtils.Marshal<bool, TValue>(IsNormalized, iinfo, ref value);
                     return;
                 }
 
                 base.GetMetadataCore(kind, iinfo, ref value);
             }
 
-            private void IsNormalized(int iinfo, ref DvBool dst)
+            private void IsNormalized(int iinfo, ref bool dst)
             {
                 Contracts.Assert(0 <= iinfo & iinfo < InfoCount);
-                dst = DvBool.True;
+                dst = true;
             }
 
             public Func<int, bool> GetDependencies(Func<int, bool> predicate)
diff --git a/src/Microsoft.ML.Data/Transforms/KeyToVectorTransform.cs b/src/Microsoft.ML.Data/Transforms/KeyToVectorTransform.cs
index 0f4b616a49..cb916a6693 100644
--- a/src/Microsoft.ML.Data/Transforms/KeyToVectorTransform.cs
+++ b/src/Microsoft.ML.Data/Transforms/KeyToVectorTransform.cs
@@ -324,7 +324,7 @@ private static void ComputeType(KeyToVectorTransform trans, ISchema input, int i
                 }
 
                 if (!bag || info.TypeSrc.ValueCount == 1)
-                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, DvBool.True);
+                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, true);
             }
         }
 
diff --git a/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs b/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs
index a7672b5a1c..81882ac749 100644
--- a/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs
+++ b/src/Microsoft.ML.Data/Transforms/LabelIndicatorTransform.cs
@@ -174,7 +174,7 @@ protected override Delegate GetGetterCore(IChannel ch, IRow input,
             return GetGetter(ch, input, iinfo);
         }
 
-        private ValueGetter<DvBool> GetGetter(IChannel ch, IRow input, int iinfo)
+        private ValueGetter<bool> GetGetter(IChannel ch, IRow input, int iinfo)
         {
             Host.AssertValue(ch);
             ch.AssertValue(input);
@@ -190,7 +190,7 @@ private ValueGetter<DvBool> GetGetter(IChannel ch, IRow input, int iinfo)
                 uint cls = (uint)(_classIndex[iinfo] + 1);
 
                 return
-                    (ref DvBool dst) =>
+                    (ref bool dst) =>
                     {
                         srcGetter(ref src);
                         dst = src == cls;
@@ -202,7 +202,7 @@ private ValueGetter<DvBool> GetGetter(IChannel ch, IRow input, int iinfo)
                 var src = default(float);
 
                 return
-                    (ref DvBool dst) =>
+                    (ref bool dst) =>
                     {
                         srcGetter(ref src);
                         dst = src == _classIndex[iinfo];
@@ -214,7 +214,7 @@ private ValueGetter<DvBool> GetGetter(IChannel ch, IRow input, int iinfo)
                 var src = default(double);
 
                 return
-                    (ref DvBool dst) =>
+                    (ref bool dst) =>
                     {
                         srcGetter(ref src);
                         dst = src == _classIndex[iinfo];
diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs b/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs
index a01b584a97..5b827b9904 100644
--- a/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs
+++ b/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs
@@ -596,7 +596,7 @@ public override void AttachMetadata(MetadataDispatcher.Builder bldr, ColumnType
                     Host.Check(typeSrc.RawType == typeof(TFloat));
                     bldr.AddPrimitive("CdfMean", typeSrc, Mean);
                     bldr.AddPrimitive("CdfStdDev", typeSrc, Stddev);
-                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, (DvBool)UseLog);
+                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, (bool)UseLog);
                 }
             }
 
@@ -625,7 +625,7 @@ public override void AttachMetadata(MetadataDispatcher.Builder bldr, ColumnType
                     Host.Check(typeSrc.ItemType.RawType == typeof(TFloat));
                     bldr.AddGetter<VBuffer<TFloat>>("CdfMean", typeSrc, MeanMetadataGetter);
                     bldr.AddGetter<VBuffer<TFloat>>("CdfStdDev", typeSrc, StddevMetadataGetter);
-                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, (DvBool)UseLog);
+                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, (bool)UseLog);
                 }
 
                 private void MeanMetadataGetter(int col, ref VBuffer<TFloat> dst)
diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeTransform.cs b/src/Microsoft.ML.Data/Transforms/NormalizeTransform.cs
index bf9d77ed49..323159f7e2 100644
--- a/src/Microsoft.ML.Data/Transforms/NormalizeTransform.cs
+++ b/src/Microsoft.ML.Data/Transforms/NormalizeTransform.cs
@@ -340,7 +340,7 @@ private void SetMetadata()
                 using (var bldr = md.BuildMetadata(iinfo, Source.Schema, Infos[iinfo].Source,
                     MetadataUtils.Kinds.SlotNames))
                 {
-                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, DvBool.True);
+                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, true);
                     _functions[iinfo].AttachMetadata(bldr, Infos[iinfo].TypeSrc);
                 }
             }
@@ -451,7 +451,6 @@ public static CommonOutputs.TransformOutput SupervisedBin(IHostEnvironment env,
             EntryPointNode node)
         {
             var schema = input.Data.Schema;
-            DvBool isNormalized = DvBool.False;
             var columnsToNormalize = new List<NormalizeTransform.AffineColumn>();
             foreach (var column in input.Column)
             {
diff --git a/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs b/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs
index e9f5f326f6..d3de0d60de 100644
--- a/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs
+++ b/src/Microsoft.ML.FastTree/TreeEnsembleFeaturizer.cs
@@ -135,7 +135,7 @@ public void GetMetadata<TValue>(string kind, int col, ref TValue value)
                     _ectx.CheckParam(0 <= col && col < ColumnCount, nameof(col));
 
                     if ((col == PathIdx || col == LeafIdx) && kind == MetadataUtils.Kinds.IsNormalized)
-                        MetadataUtils.Marshal<DvBool, TValue>(IsNormalized, col, ref value);
+                        MetadataUtils.Marshal<bool, TValue>(IsNormalized, col, ref value);
                     else if (kind == MetadataUtils.Kinds.SlotNames)
                     {
                         switch (col)
@@ -156,9 +156,9 @@ public void GetMetadata<TValue>(string kind, int col, ref TValue value)
                         throw _ectx.ExceptGetMetadata();
                 }
 
-                private void IsNormalized(int iinfo, ref DvBool dst)
+                private void IsNormalized(int iinfo, ref bool dst)
                 {
-                    dst = DvBool.True;
+                    dst = true;
                 }
             }
 
diff --git a/src/Microsoft.ML.Parquet/ParquetLoader.cs b/src/Microsoft.ML.Parquet/ParquetLoader.cs
index 503debae65..a5413c4d7a 100644
--- a/src/Microsoft.ML.Parquet/ParquetLoader.cs
+++ b/src/Microsoft.ML.Parquet/ParquetLoader.cs
@@ -495,7 +495,7 @@ private Delegate CreateGetterDelegate(int col)
                 switch (parquetType)
                 {
                     case DataType.Boolean:
-                        return CreateGetterDelegateCore<bool?, DvBool>(col, _parquetConversions.Conv);
+                        return CreateGetterDelegateCore<bool, bool>(col, _parquetConversions.Conv);
                     case DataType.Byte:
                         return CreateGetterDelegateCore<byte, byte>(col, _parquetConversions.Conv);
                     case DataType.SignedByte:
@@ -698,7 +698,8 @@ public ParquetConversions(IChannel channel)
 
             public void Conv(ref string src, ref DvText dst) => dst = new DvText(src);
 
-            public void Conv(ref bool? src, ref DvBool dst) => dst = src ?? DvBool.NA;
+            //Behavior for NA values is undefined.
+            public void Conv(ref bool src, ref bool dst) => dst = src;
 
             public void Conv(ref DateTimeOffset src, ref DvDateTimeZone dst) => dst = src;
 
diff --git a/src/Microsoft.ML.PipelineInference/ColumnTypeInference.cs b/src/Microsoft.ML.PipelineInference/ColumnTypeInference.cs
index 0d880c7d41..6cd0ff9d52 100644
--- a/src/Microsoft.ML.PipelineInference/ColumnTypeInference.cs
+++ b/src/Microsoft.ML.PipelineInference/ColumnTypeInference.cs
@@ -132,7 +132,7 @@ public void Apply(IntermediateColumn[] columns)
                         if (!col.RawData.Skip(1)
                             .All(x =>
                                 {
-                                    DvBool value;
+                                    bool value;
                                     return Conversions.Instance.TryParse(ref x, out value);
                                 })
                             )
@@ -141,7 +141,7 @@ public void Apply(IntermediateColumn[] columns)
                         }
 
                         col.SuggestedType = BoolType.Instance;
-                        DvBool first;
+                        bool first;
 
                         col.HasHeader = !Conversions.Instance.TryParse(ref col.RawData[0], out first);
                     }
diff --git a/src/Microsoft.ML.Transforms/GcnTransform.cs b/src/Microsoft.ML.Transforms/GcnTransform.cs
index c9b8398814..29af56bb98 100644
--- a/src/Microsoft.ML.Transforms/GcnTransform.cs
+++ b/src/Microsoft.ML.Transforms/GcnTransform.cs
@@ -413,7 +413,7 @@ private void SetMetadata()
             for (int iinfo = 0; iinfo < Infos.Length; iinfo++)
             {
                 using (var bldr = md.BuildMetadata(iinfo, Source.Schema, Infos[iinfo].Source, MetadataUtils.Kinds.SlotNames))
-                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, DvBool.True);
+                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, true);
             }
             md.Seal();
         }
diff --git a/src/Microsoft.ML.Transforms/KeyToBinaryVectorTransform.cs b/src/Microsoft.ML.Transforms/KeyToBinaryVectorTransform.cs
index 88a4228941..7a96f2d96d 100644
--- a/src/Microsoft.ML.Transforms/KeyToBinaryVectorTransform.cs
+++ b/src/Microsoft.ML.Transforms/KeyToBinaryVectorTransform.cs
@@ -166,7 +166,7 @@ private static void ComputeType(KeyToBinaryVectorTransform trans, ISchema input,
                             new VectorType(TextType.Instance, type), trans.GetKeyNames);
                     }
 
-                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, DvBool.True);
+                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, true);
                 }
                 else
                 {
diff --git a/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs b/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs
index 0af833a046..f160d42540 100644
--- a/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs
+++ b/src/Microsoft.ML.Transforms/MutualInformationFeatureSelection.cs
@@ -300,7 +300,7 @@ private sealed class Impl
             private int[] _featureSums;
             private readonly List<Single> _singles;
             private readonly List<Double> _doubles;
-            private ValueMapper<VBuffer<DvBool>, VBuffer<int>> _boolMapper;
+            private ValueMapper<VBuffer<bool>, VBuffer<int>> _boolMapper;
 
             public Impl(IHost host)
             {
@@ -428,7 +428,7 @@ private void GetLabels(Transposer trans, ColumnType labelType, int labelCol)
                 }
                 else if (labelType.IsBool)
                 {
-                    var tmp = default(VBuffer<DvBool>);
+                    var tmp = default(VBuffer<bool>);
                     trans.GetSingleSlotValue(labelCol, ref tmp);
                     BinBools(ref tmp, ref labels);
                     _numLabels = 3;
@@ -510,7 +510,7 @@ private Single[] ComputeMutualInformation(Transposer trans, int col)
                 if (type.ItemType.IsBool)
                 {
                     return ComputeMutualInformation(trans, col,
-                        (ref VBuffer<DvBool> src, ref VBuffer<int> dst, out int min, out int lim) =>
+                        (ref VBuffer<bool> src, ref VBuffer<int> dst, out int min, out int lim) =>
                         {
                             min = -1;
                             lim = 2;
@@ -756,16 +756,16 @@ private void BinDoubles(ref VBuffer<Double> input, ref VBuffer<int> output,
                 _doubles.Clear();
             }
 
-            private void BinBools(ref VBuffer<DvBool> input, ref VBuffer<int> output)
+            private void BinBools(ref VBuffer<bool> input, ref VBuffer<int> output)
             {
                 if (_boolMapper == null)
-                    _boolMapper = CreateVectorMapper<DvBool, int>(BinOneBool);
+                    _boolMapper = CreateVectorMapper<bool, int>(BinOneBool);
                 _boolMapper(ref input, ref output);
             }
 
-            private void BinOneBool(ref DvBool src, ref int dst)
+            private void BinOneBool(ref bool src, ref int dst)
             {
-                dst = src.IsNA ? -1 : src.IsFalse ? 0 : 1;
+                dst = Convert.ToInt32(src);
             }
         }
 
diff --git a/src/Microsoft.ML.Transforms/NADropTransform.cs b/src/Microsoft.ML.Transforms/NADropTransform.cs
index 80e88f3ae3..ea47fb9d1a 100644
--- a/src/Microsoft.ML.Transforms/NADropTransform.cs
+++ b/src/Microsoft.ML.Transforms/NADropTransform.cs
@@ -100,7 +100,7 @@ private Delegate[] InitIsNAAndMetadata()
                     MetadataUtils.Kinds.IsNormalized, MetadataUtils.Kinds.KeyValues))
                 {
                     // Output does not have missings.
-                    bldr.AddPrimitive(MetadataUtils.Kinds.HasMissingValues, BoolType.Instance, DvBool.False);
+                    bldr.AddPrimitive(MetadataUtils.Kinds.HasMissingValues, BoolType.Instance, false);
                 }
             }
             md.Seal();
diff --git a/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs b/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs
index 7607e19c61..950a8ccce3 100644
--- a/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs
+++ b/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs
@@ -156,7 +156,7 @@ private ColumnType[] GetTypesAndMetadata()
                 using (var bldr = md.BuildMetadata(iinfo, Source.Schema, Infos[iinfo].Source, MetadataUtils.Kinds.SlotNames))
                 {
                     // Output is normalized.
-                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, DvBool.True);
+                    bldr.AddPrimitive(MetadataUtils.Kinds.IsNormalized, BoolType.Instance, true);
                 }
             }
             md.Seal();
@@ -184,41 +184,41 @@ protected override Delegate GetGetterCore(IChannel ch, IRow input, int iinfo, ou
         /// <summary>
         /// Getter generator for single valued inputs.
         /// </summary>
-        private ValueGetter<DvBool> ComposeGetterOne(IRow input, int iinfo)
+        private ValueGetter<bool> ComposeGetterOne(IRow input, int iinfo)
         {
-            Func<IRow, int, ValueGetter<DvBool>> func = ComposeGetterOne<int>;
+            Func<IRow, int, ValueGetter<bool>> func = ComposeGetterOne<int>;
             return Utils.MarshalInvoke(func, Infos[iinfo].TypeSrc.RawType, input, iinfo);
         }
 
         /// <summary>
         ///  Tests if a value is NA for scalars.
         /// </summary>
-        private ValueGetter<DvBool> ComposeGetterOne<T>(IRow input, int iinfo)
+        private ValueGetter<bool> ComposeGetterOne<T>(IRow input, int iinfo)
         {
             var getSrc = GetSrcGetter<T>(input, iinfo);
             var isNA = Conversions.Instance.GetIsNAPredicate<T>(input.Schema.GetColumnType(Infos[iinfo].Source));
             T src = default(T);
             return
-                (ref DvBool dst) =>
+                (ref bool dst) =>
                 {
                     getSrc(ref src);
-                    dst = isNA(ref src) ? DvBool.True : DvBool.False;
+                    dst = isNA(ref src);
                 };
         }
 
         /// <summary>
         /// Getter generator for vector valued inputs.
         /// </summary>
-        private ValueGetter<VBuffer<DvBool>> ComposeGetterVec(IRow input, int iinfo)
+        private ValueGetter<VBuffer<bool>> ComposeGetterVec(IRow input, int iinfo)
         {
-            Func<IRow, int, ValueGetter<VBuffer<DvBool>>> func = ComposeGetterVec<int>;
+            Func<IRow, int, ValueGetter<VBuffer<bool>>> func = ComposeGetterVec<int>;
             return Utils.MarshalInvoke(func, Infos[iinfo].TypeSrc.ItemType.RawType, input, iinfo);
         }
 
         /// <summary>
         ///  Tests if a value is NA for vectors.
         /// </summary>
-        private ValueGetter<VBuffer<DvBool>> ComposeGetterVec<T>(IRow input, int iinfo)
+        private ValueGetter<VBuffer<bool>> ComposeGetterVec<T>(IRow input, int iinfo)
         {
             var getSrc = GetSrcGetter<VBuffer<T>>(input, iinfo);
             var isNA = Conversions.Instance.GetIsNAPredicate<T>(input.Schema.GetColumnType(Infos[iinfo].Source).ItemType);
@@ -227,7 +227,7 @@ private ValueGetter<VBuffer<DvBool>> ComposeGetterVec<T>(IRow input, int iinfo)
             var src = default(VBuffer<T>);
             var indices = new List<int>();
             return
-                (ref VBuffer<DvBool> dst) =>
+                (ref VBuffer<bool> dst) =>
                 {
                     // Sense indicates if the values added to the indices list represent NAs or non-NAs.
                     bool sense;
@@ -285,7 +285,7 @@ private void FindNAs<T>(ref VBuffer<T> src, RefPredicate<T> isNA, bool defaultIs
         ///  Fills indicator values for vectors.  The indices is a list that either holds all of the NAs or all
         ///  of the non-NAs, indicated by sense being true or false respectively.
         /// </summary>
-        private void FillValues(int srcLength, ref VBuffer<DvBool> dst, List<int> indices, bool sense)
+        private void FillValues(int srcLength, ref VBuffer<bool> dst, List<int> indices, bool sense)
         {
             var dstValues = dst.Values;
             var dstIndices = dst.Indices;
@@ -295,15 +295,15 @@ private void FillValues(int srcLength, ref VBuffer<DvBool> dst, List<int> indice
                 if (sense)
                 {
                     // Return empty VBuffer.
-                    dst = new VBuffer<DvBool>(srcLength, 0, dstValues, dstIndices);
+                    dst = new VBuffer<bool>(srcLength, 0, dstValues, dstIndices);
                     return;
                 }
 
                 // Return VBuffer filled with 1's.
                 Utils.EnsureSize(ref dstValues, srcLength, false);
                 for (int i = 0; i < srcLength; i++)
-                    dstValues[i] = DvBool.True;
-                dst = new VBuffer<DvBool>(srcLength, dstValues, dstIndices);
+                    dstValues[i] = true;
+                dst = new VBuffer<bool>(srcLength, dstValues, dstIndices);
                 return;
             }
 
@@ -316,10 +316,10 @@ private void FillValues(int srcLength, ref VBuffer<DvBool> dst, List<int> indice
 
                 indices.CopyTo(dstIndices);
                 for (int ii = 0; ii < dstCount; ii++)
-                    dstValues[ii] = DvBool.True;
+                    dstValues[ii] = true;
 
                 Host.Assert(dstCount <= srcLength);
-                dst = new VBuffer<DvBool>(srcLength, dstCount, dstValues, dstIndices);
+                dst = new VBuffer<bool>(srcLength, dstCount, dstValues, dstIndices);
             }
             else if (!sense && srcLength - indices.Count < srcLength / 2)
             {
@@ -342,7 +342,7 @@ private void FillValues(int srcLength, ref VBuffer<DvBool> dst, List<int> indice
                     if (i < iNext)
                     {
                         Host.Assert(iiDst < dstCount);
-                        dstValues[iiDst] = DvBool.True;
+                        dstValues[iiDst] = true;
                         dstIndices[iiDst++] = i;
                     }
                     else
@@ -355,7 +355,7 @@ private void FillValues(int srcLength, ref VBuffer<DvBool> dst, List<int> indice
                 Host.Assert(srcLength == iiSrc + iiDst);
                 Host.Assert(iiDst == dstCount);
 
-                dst = new VBuffer<DvBool>(srcLength, dstCount, dstValues, dstIndices);
+                dst = new VBuffer<bool>(srcLength, dstCount, dstValues, dstIndices);
             }
             else
             {
@@ -368,8 +368,8 @@ private void FillValues(int srcLength, ref VBuffer<DvBool> dst, List<int> indice
 
                 int ii = 0;
                 // Assigns values correctly depending on the sense.
-                DvBool hit = sense ? DvBool.True : DvBool.False;
-                DvBool miss = sense ? DvBool.False : DvBool.True;
+                bool hit = sense;
+                bool miss = !sense;
                 for (int i = 0; i < srcLength; i++)
                 {
                     Host.Assert(0 <= i && i <= indices[ii]);
@@ -384,7 +384,7 @@ private void FillValues(int srcLength, ref VBuffer<DvBool> dst, List<int> indice
                         dstValues[i] = miss;
                 }
 
-                dst = new VBuffer<DvBool>(srcLength, dstValues, dstIndices);
+                dst = new VBuffer<bool>(srcLength, dstValues, dstIndices);
             }
         }
     }
diff --git a/src/Microsoft.ML/Data/TextLoader.cs b/src/Microsoft.ML/Data/TextLoader.cs
index 330412185e..0deb1ce5c3 100644
--- a/src/Microsoft.ML/Data/TextLoader.cs
+++ b/src/Microsoft.ML/Data/TextLoader.cs
@@ -182,7 +182,7 @@ private static bool TryGetDataKind(Type type, out DataKind kind)
                 kind = DataKind.R8;
             else if (type == typeof(DvText) || type == typeof(string))
                 kind = DataKind.TX;
-            else if (type == typeof(DvBool) || type == typeof(bool))
+            else if (type == typeof(bool))
                 kind = DataKind.BL;
             else if (type == typeof(DvTimeSpan) || type == typeof(TimeSpan))
                 kind = DataKind.TS;
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt
index eb8fd43aae..e3b32ab1be 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	3.64133739	1	0	1
 35	0	-2.796535	1E-15	1.4415419267167138E-15	0
 37	0	-1.65404248	1E-15	1.4415419267167138E-15	0
-40	0				
+40	0				0
 41	1	1.04337406	0.8947368	0.16046469748481262	1
 44	1	4.33966541	1	0	1
 45	0	-2.89273548	1E-15	1.4415419267167138E-15	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-2.35179329	1E-15	1.4415419267167138E-15	0
 141	0	-2.904073	1E-15	1.4415419267167138E-15	0
 144	0	-2.796535	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 147	0	-2.463921	1E-15	1.4415419267167138E-15	0
 150	0	-2.8614285	1E-15	1.4415419267167138E-15	0
 151	1	3.17632246	1	0	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-3.01920986	1E-15	1.4415419267167138E-15	0
 156	0	-2.49565363	1E-15	1.4415419267167138E-15	0
 161	0	-2.30924	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 167	1	2.38255262	0.8947368	0.16046469748481262	1
 169	0	-3.03097248	1E-15	1.4415419267167138E-15	0
 171	0	-2.804134	1E-15	1.4415419267167138E-15	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	7.227234	1	0	1
 247	1	2.672493	0.8947368	0.16046469748481262	1
 248	0	-1.711307	1E-15	1.4415419267167138E-15	0
-249	0				
+249	0				0
 250	0	-2.60319138	1E-15	1.4415419267167138E-15	0
 252	0	2.992918	0.8947368	3.2479272984652883	1
 254	1	5.35164165	1	0	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-2.804134	1E-15	1.4415419267167138E-15	0
 271	0	-2.34358668	1E-15	1.4415419267167138E-15	0
 272	1	2.73419476	0.8947368	0.16046469748481262	1
-275	0				
+275	0				0
 276	0	-2.68139815	1E-15	1.4415419267167138E-15	0
 277	0	-2.91167164	1E-15	1.4415419267167138E-15	0
 278	0	-2.804134	1E-15	1.4415419267167138E-15	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-2.804134	1E-15	1.4415419267167138E-15	0
 293	1	3.413344	1	0	1
 296	0	1.47483253	0.8947368	3.2479272984652883	1
-297	0				
+297	0				0
 299	1	3.53376913	1	0	1
 300	1	3.78027344	1	0	1
 301	0	-2.804134	1E-15	1.4415419267167138E-15	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.45851088	1	0	1
 317	1	5.48386	1	0	1
 319	0	1.44604874	0.8947368	3.2479272984652883	1
-321	0				
+321	0				0
 323	1	3.36483288	1	0	1
 327	0	-2.91167164	1E-15	1.4415419267167138E-15	0
 328	1	3.03614	0.8947368	0.16046469748481262	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	8.167599	1	0	1
 613	0	-2.39343452	1E-15	1.4415419267167138E-15	0
 614	0	-2.85382986	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-2.56626129	1E-15	1.4415419267167138E-15	0
 619	0	-2.45112467	1E-15	1.4415419267167138E-15	0
 621	0	-0.5349846	0.2	0.32192810026182023	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-2.27471757	1E-15	1.4415419267167138E-15	0
 19	0	-2.00358748	1E-15	1.4415419267167138E-15	0
 22	0	-2.5426836	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-2.68141246	1E-15	1.4415419267167138E-15	0
 26	0	-2.33200574	1E-15	1.4415419267167138E-15	0
 27	0	-2.27155375	1E-15	1.4415419267167138E-15	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-2.546271	1E-15	1.4415419267167138E-15	0
 135	0	-1.52827668	1E-15	1.4415419267167138E-15	0
 136	0	-2.40711856	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-2.67508459	1E-15	1.4415419267167138E-15	0
 142	1	2.1587286	0.9117647	0.13326656969825684	1
 143	0	-1.54474568	1E-15	1.4415419267167138E-15	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.83878517	1E-15	1.4415419267167138E-15	0
 155	1	3.237853	0.9117647	0.13326656969825684	1
 157	0	-2.54584742	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	6.77223158	1	0	1
 160	1	5.42115831	1	0	1
 162	0	-2.41028237	1E-15	1.4415419267167138E-15	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.187345	1	0	1
 232	0	0.397937775	0.714285731	1.8073550080489322	1
 234	0	-1.183644	1E-15	1.4415419267167138E-15	0
-235	0				
+235	0				0
 236	1	5.6324296	1	0	1
 238	1	6.77774	1	0	1
 243	0	-1.01514125	1E-15	1.4415419267167138E-15	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	7.8132205	1	0	1
 287	0	-2.546271	1E-15	1.4415419267167138E-15	0
 289	1	5.25516939	1	0	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77293825	1	0	1
 298	0	-1.80093193	1E-15	1.4415419267167138E-15	0
 302	1	7.77011251	1	0	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-2.68141246	1E-15	1.4415419267167138E-15	0
 310	0	-2.68183613	1E-15	1.4415419267167138E-15	0
 313	0	-2.94621468	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 318	0	-2.69217515	1E-15	1.4415419267167138E-15	0
 320	1	3.800508	0.9444444	0.082462200658479604	1
 322	0	-2.41028237	1E-15	1.4415419267167138E-15	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.81381369	1E-15	1.4415419267167138E-15	0
 408	0	-1.46855927	1E-15	1.4415419267167138E-15	0
 410	0	-2.81381369	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	4.83788157	1	0	1
 417	0	-2.81381369	1E-15	1.4415419267167138E-15	0
 420	0	-1.04175115	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt
index 3b51cd60d5..31cb0b05b4 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	3.64133739	0.9844741	0.022574810341618422	1
 35	0	-2.796535	0.0199539755	0.029078592776682857	0
 37	0	-1.65404248	0.0782266259	0.11751599963260938	0
-40	0				
+40	0				0
 41	1	1.04337406	0.7116856	0.49068805388019454	1
 44	1	4.33966541	0.9934526	0.0094769477341525628	1
 45	0	-2.89273548	0.0177341755	0.025814589979333783	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-2.35179329	0.03427408	0.050314293386144675	0
 141	0	-2.904073	0.0174890943	0.025454673744601461	0
 144	0	-2.796535	0.0199539755	0.029078592776682857	0
-145	0				
+145	0				0
 147	0	-2.463921	0.0299276374	0.04383572570114834	0
 150	0	-2.8614285	0.01842858	0.026834852844454766	0
 151	1	3.17632246	0.9725775	0.040114860620962978	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-3.01920986	0.0151813291	0.022069981158425081	0
 156	0	-2.49565363	0.0287977811	0.042156377165560456	0
 161	0	-2.30924	0.0360781476	0.053011906638395674	0
-164	0				
+164	0				0
 167	1	2.38255262	0.9293544	0.10569919063924076	1
 169	0	-3.03097248	0.0149631584	0.021750410734051751	0
 171	0	-2.804134	0.0197691489	0.028806541052408416	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	7.227234	0.999821365	0.00025773902362411926	1
 247	1	2.672493	0.9497448	0.074388155670230882	1
 248	0	-1.711307	0.07322063	0.10970216917333013	0
-249	0				
+249	0				0
 250	0	-2.60319138	0.0252686124	0.036923393165046718	0
 252	0	2.992918	0.9657571	4.8680501214754637	1
 254	1	5.35164165	0.998142242	0.0026826702788205732	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-2.804134	0.0197691489	0.028806541052408416	0
 271	0	-2.34358668	0.0346150957	0.050823827322496622	0
 272	1	2.73419476	0.9532994	0.068998701675288501	1
-275	0				
+275	0				0
 276	0	-2.68139815	0.0229703225	0.033525709865030048	0
 277	0	-2.91167164	0.0173267	0.025216237008576704	0
 278	0	-2.804134	0.0197691489	0.028806541052408416	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-2.804134	0.0197691489	0.028806541052408416	0
 293	1	3.413344	0.9794621	0.029938444898768346	1
 296	0	1.47483253	0.8088676	2.3873555377194497	1
-297	0				
+297	0				0
 299	1	3.53376913	0.982280254	0.025793396317687449	1
 300	1	3.78027344	0.986915946	0.019000876915907086	1
 301	0	-2.804134	0.0197691489	0.028806541052408416	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.45851088	0.980567157	0.028311653515975352	1
 317	1	5.48386	0.9984247	0.0022744566762884174	1
 319	0	1.44604874	0.803245664	2.3455326626007635	1
-321	0				
+321	0				0
 323	1	3.36483288	0.978206754	0.031788669528507826	1
 327	0	-2.91167164	0.0173267	0.025216237008576704	0
 328	1	3.03614	0.9674988	0.047668253892284254	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	8.167599	0.9999448	7.9630164919418245E-05	1
 613	0	-2.39343452	0.03259308	0.047805235639227908	0
 614	0	-2.85382986	0.0186011065	0.027088450049153875	0
-617	0				
+617	0				0
 618	0	-2.56626129	0.02643034	0.038643886518904186	0
 619	0	-2.45112467	0.0303953178	0.044531429350354604	0
 621	0	-0.5349846	0.255690753	0.42602593625059765	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-2.27471757	0.0249303821	0.036422867055812318	0
 19	0	-2.00358748	0.03410183	0.050056992617068342	0
 22	0	-2.5426836	0.0182464458	0.026567179066779304	0
-23	1				
+23	1				0
 24	0	-2.68141246	0.015512228	0.022554807909292037	0
 26	0	-2.33200574	0.02332543	0.034050161954667077	0
 27	0	-2.27155375	0.0250220858	0.036558556406276949	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-2.546271	0.0181701127	0.026455011357386121	0
 135	0	-1.52827668	0.0585265532	0.087007689086403689	0
 136	0	-2.40711856	0.0213731956	0.031169296396687675	0
-139	0				
+139	0				0
 140	0	-2.67508459	0.015627671	0.022723991158114246	0
 142	1	2.1587286	0.83348304	0.26277525125659912	1
 143	0	-1.54474568	0.05745574	0.085367730161702821	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.83878517	0.0411879122	0.060679997683715341	0
 155	1	3.237853	0.947596252	0.077655602601770859	1
 157	0	-2.54584742	0.0181791112	0.026468233670711376	0
-158	0				
+158	0				0
 159	1	6.77223158	0.999177039	0.0011877710421138682	1
 160	1	5.42115831	0.995904	0.0059213730758132374	1
 162	0	-2.41028237	0.0212945715	0.031053393109467146	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.187345	0.9945968	0.0078163354020312284	1
 232	0	0.397937775	0.381006956	0.69200489802945642	1
 234	0	-1.183644	0.085664086	0.12920380666492423	0
-235	0				
+235	0				0
 236	1	5.6324296	0.9968118	0.0046069378176225089	1
 238	1	6.77774	0.9991824	0.0011800254692933552	1
 243	0	-1.01514125	0.102734588	0.15639329612707187	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	7.8132205	0.999761462	0.00034417833577817593	1
 287	0	-2.546271	0.0181701127	0.026455011357386121	0
 289	1	5.25516939	0.9950138	0.0072115986401722143	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77293825	0.9911819	0.012778237651616852	1
 298	0	-1.80093193	0.0430044457	0.063415872213561694	0
 302	1	7.77011251	0.999748945	0.00036224093577622284	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-2.68141246	0.015512228	0.022554807909292037	0
 310	0	-2.68183613	0.0155045288	0.022543525273161929	0
 313	0	-2.94621468	0.0113662509	0.016491938164477051	0
-315	0				
+315	0				0
 318	0	-2.69217515	0.0153178023	0.022269919361612874	0
 320	1	3.800508	0.9724724	0.040270746291192143	1
 322	0	-2.41028237	0.0212945715	0.031053393109467146	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.81381369	0.0132805621	0.019288165348886492	0
 408	0	-1.46855927	0.06256822	0.093214386421141548	0
 410	0	-2.81381369	0.0132805621	0.019288165348886492	0
-411	0				
+411	0				0
 412	1	4.83788157	0.991832554	0.011831516022545778	1
 417	0	-2.81381369	0.0132805621	0.019288165348886492	0
 420	0	-1.04175115	0.09985152	0.15176509864238413	0
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt
index 09a2fb9aa7..afd5a0dfc0 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Assigned
 32	1	3.64133739	1
 35	0	-2.796535	0
 37	0	-1.65404248	0
-40	0		
+40	0		0
 41	1	1.04337406	1
 44	1	4.33966541	1
 45	0	-2.89273548	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Assigned
 138	0	-2.35179329	0
 141	0	-2.904073	0
 144	0	-2.796535	0
-145	0		
+145	0		0
 147	0	-2.463921	0
 150	0	-2.8614285	0
 151	1	3.17632246	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Assigned
 154	0	-3.01920986	0
 156	0	-2.49565363	0
 161	0	-2.30924	0
-164	0		
+164	0		0
 167	1	2.38255262	1
 169	0	-3.03097248	0
 171	0	-2.804134	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Assigned
 246	1	7.227234	1
 247	1	2.672493	1
 248	0	-1.711307	0
-249	0		
+249	0		0
 250	0	-2.60319138	0
 252	0	2.992918	1
 254	1	5.35164165	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Assigned
 269	0	-2.804134	0
 271	0	-2.34358668	0
 272	1	2.73419476	1
-275	0		
+275	0		0
 276	0	-2.68139815	0
 277	0	-2.91167164	0
 278	0	-2.804134	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Assigned
 291	0	-2.804134	0
 293	1	3.413344	1
 296	0	1.47483253	1
-297	0		
+297	0		0
 299	1	3.53376913	1
 300	1	3.78027344	1
 301	0	-2.804134	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Assigned
 316	1	3.45851088	1
 317	1	5.48386	1
 319	0	1.44604874	1
-321	0		
+321	0		0
 323	1	3.36483288	1
 327	0	-2.91167164	0
 328	1	3.03614	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Assigned
 612	1	8.167599	1
 613	0	-2.39343452	0
 614	0	-2.85382986	0
-617	0		
+617	0		0
 618	0	-2.56626129	0
 619	0	-2.45112467	0
 621	0	-0.5349846	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Assigned
 17	0	-2.27471757	0
 19	0	-2.00358748	0
 22	0	-2.5426836	0
-23	1		
+23	1		0
 24	0	-2.68141246	0
 26	0	-2.33200574	0
 27	0	-2.27155375	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Assigned
 134	0	-2.546271	0
 135	0	-1.52827668	0
 136	0	-2.40711856	0
-139	0		
+139	0		0
 140	0	-2.67508459	0
 142	1	2.1587286	1
 143	0	-1.54474568	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Assigned
 153	0	-1.83878517	0
 155	1	3.237853	1
 157	0	-2.54584742	0
-158	0		
+158	0		0
 159	1	6.77223158	1
 160	1	5.42115831	1
 162	0	-2.41028237	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Assigned
 231	1	5.187345	1
 232	0	0.397937775	1
 234	0	-1.183644	0
-235	0		
+235	0		0
 236	1	5.6324296	1
 238	1	6.77774	1
 243	0	-1.01514125	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Assigned
 286	1	7.8132205	1
 287	0	-2.546271	0
 289	1	5.25516939	1
-292	1		
-294	0		
+292	1		0
+294	0		0
 295	1	4.77293825	1
 298	0	-1.80093193	0
 302	1	7.77011251	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Assigned
 307	0	-2.68141246	0
 310	0	-2.68183613	0
 313	0	-2.94621468	0
-315	0		
+315	0		0
 318	0	-2.69217515	0
 320	1	3.800508	1
 322	0	-2.41028237	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Assigned
 407	0	-2.81381369	0
 408	0	-1.46855927	0
 410	0	-2.81381369	0
-411	0		
+411	0		0
 412	1	4.83788157	1
 417	0	-2.81381369	0
 420	0	-1.04175115	0
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt
index 693440edc2..09ce4b3736 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	2.35438	0.996385	0.0052248235129257635	1
 35	0	-1.83556986	0.00724350661	0.010488202773633042	0
 37	0	-0.8828192	0.07420456	0.11123463299619094	0
-40	0				
+40	0				0
 41	1	0.6366718	0.7855496	0.34822575879653411	1
 44	1	2.72072053	0.998558342	0.002081372862402793	1
 45	0	-1.87994158	0.00648348359	0.0093841435784006184	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.51871562	0.0159320254	0.02317012154973026	0
 141	0	-1.93865037	0.00559835136	0.0080994066187532153	0
 144	0	-1.83556986	0.00724350661	0.010488202773633042	0
-145	0				
+145	0				0
 147	0	-1.69274938	0.010342177	0.014998299390129487	0
 150	0	-1.91297352	0.00596963847	0.0086381769438633477	0
 151	1	1.55168462	0.973401248	0.038893469912665984	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-2.0423522	0.004318493	0.0062437599081359638	0
 156	0	-1.73049688	0.009414184	0.013646131293487658	0
 161	0	-1.46562588	0.0181668717	0.026450249055215744	0
-164	0				
+164	0				0
 167	1	2.31870866	0.99604696	0.0057143326416850991	1
 169	0	-2.041339	0.00432946626	0.0062596597963016712	0
 171	0	-1.8361913	0.00723227439	0.010471879968765333	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	3.8998096	0.9999256	0.00010732116581602008	1
 247	1	0.9928844	0.8997386	0.15242216136874395	1
 248	0	-1.22778583	0.03256034	0.047756414470681303	0
-249	0				
+249	0				0
 250	0	-1.83357728	0.00727963867	0.010540711608751351	0
 252	0	1.37199	0.958826959	4.6021561858199664	1
 254	1	2.79375386	0.9988	0.0017323029622904203	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.8361913	0.00723227439	0.010471879968765333	0
 271	0	-1.42138422	0.0202620383	0.02953215377914243	0
 272	1	1.10222125	0.921965	0.11721610663727763	1
-275	0				
+275	0				0
 276	0	-1.73186815	0.009382072	0.013599363941350218	0
 277	0	-1.93927169	0.00558965746	0.0080867934194779039	0
 278	0	-1.8361913	0.00723227439	0.010471879968765333	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.8361913	0.00723227439	0.010471879968765333	0
 293	1	1.65592456	0.9794098	0.030015442677317709	1
 296	0	0.553571463	0.748245	1.9899076684215853	1
-297	0				
+297	0				0
 299	1	2.001486	0.991262555	0.012660861084033199	1
 300	1	2.09417748	0.9930671	0.010036913891508983	1
 301	0	-1.8361913	0.00723227439	0.010471879968765333	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	1.47151637	0.9676506	0.047441894201880302	1
 317	1	3.06524873	0.999393463	0.00087531320929783803	1
 319	0	0.8519552	0.8629285	2.8669995609516308	1
-321	0				
+321	0				0
 323	1	1.75474	0.9838682	0.023463058122578043	1
 327	0	-1.93927169	0.00558965746	0.0080867934194779039	0
 328	1	1.43182349	0.964374959	0.052333903838185522	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	5.09431458	0.9999963	5.3314720279485219E-06	1
 613	0	-1.63692176	0.0118829105	0.017246087060301379	0
 614	0	-1.9123522	0.00597891957	0.0086516472088849234	0
-617	0				
+617	0				0
 618	0	-1.62816632	0.0121443039	0.017627783540922228	0
 619	0	-1.52446461	0.0157068819	0.022840087163427197	0
 621	0	-0.188778639	0.31474337	0.54528371301135603	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.57970572	0.0144622317	0.021016934775320784	0
 19	0	-1.32506859	0.0253080986	0.036981837697027814	0
 22	0	-1.76987159	0.009491567	0.01375883626140059	0
-23	1				
+23	1				0
 24	0	-1.96166122	0.00619609	0.0089668769102733102	0
 26	0	-1.67495286	0.0117150256	0.017000988488892345	0
 27	0	-1.51523459	0.0166727714	0.024256502854015347	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.75784481	0.009748338	0.014132877086598956	0
 135	0	-1.07198834	0.04377895	0.06458392745656516	0
 136	0	-1.64255309	0.0125861792	0.018273256294688772	0
-139	0				
+139	0				0
 140	0	-1.832719	0.008254912	0.01195874763978641	0
 142	1	1.20702124	0.8832422	0.17911900782229345	1
 143	0	-1.436229	0.0198381469	0.028908095216224419	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.37983692	0.0224505328	0.032758385480089913	0
 155	1	1.24272728	0.8912444	0.16610696969487637	1
 157	0	-1.83434272	0.008225175	0.011915489581813862	0
-158	0				
+158	0				0
 159	1	4.09360933	0.999795	0.00029575448112624953	1
 160	1	3.04705143	0.997864842	0.0030836744978663621	1
 162	0	-1.70702422	0.0109114433	0.015828398337213719	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	2.80366325	0.996321738	0.0053163942348769758	1
 232	0	0.248882532	0.46910888	0.91351208341864276	1
 234	0	-0.8223932	0.0741594	0.11116426368346338	0
-235	0				
+235	0				0
 236	1	3.65436459	0.999451637	0.00079133718371403176	1
 238	1	4.208801	0.99984163	0.00022849704563499302	1
 243	0	-1.18483961	0.0343320966	0.050400968413634589	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	4.869809	0.999964	5.1939695512002597E-05	1
 287	0	-1.75784481	0.009748338	0.014132877086598956	0
 289	1	2.8387928	0.996599257	0.0049145964567919058	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	2.21859837	0.9864867	0.019628533461458434	1
 298	0	-1.053101	0.0455854833	0.067312108231381534	0
 302	1	4.847371	0.999962151	5.4605525036338512E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.96166122	0.00619609	0.0089668769102733102	0
 310	0	-1.88516331	0.007346285	0.010637570327263628	0
 313	0	-2.087356	0.00468213623	0.0067707579292392971	0
-315	0				
+315	0				0
 318	0	-1.9255811	0.006714394	0.00971948958962956	0
 320	1	1.98424911	0.9773634	0.03303300364958086	1
 322	0	-1.70702422	0.0109114433	0.015828398337213719	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.02450848	0.00538646942	0.0077920373965741406	0
 408	0	-1.276682	0.0281251986	0.041157619505191562	0
 410	0	-2.02450848	0.00538646942	0.0077920373965741406	0
-411	0				
+411	0				0
 412	1	2.820312	0.996455967	0.0051220399276606741	1
 417	0	-2.02450848	0.00538646942	0.0077920373965741406	0
 420	0	-1.02720916	0.0481775925	0.071235676455785449	0
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt
index 0c2f376b8f..a617fa7a4c 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	4.309107	0.9756098	0.035623875334191583	1
 21	1	6.161626	1	0	1
 22	0	-3.35177135	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-3.57612	1E-15	1.4415419267167138E-15	0
 25	1	1.68778992	0.8125	0.29956028185890782	1
 26	0	-3.21128821	1E-15	1.4415419267167138E-15	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.20465565	0.0625	0.093109404391481479	0
 38	1	4.3035	0.9756098	0.035623875334191583	1
 39	1	2.444232	0.84	0.25153881203904033	1
-40	0				
+40	0				0
 41	1	2.349327	0.84	0.25153881203904033	1
 42	1	6.69547653	1	0	1
 43	1	0.1725626	0.7777778	0.36257005481575838	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-3.11112714	1E-15	1.4415419267167138E-15	0
 137	0	-3.60871148	1E-15	1.4415419267167138E-15	0
 138	0	-2.89319158	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-3.60871148	1E-15	1.4415419267167138E-15	0
 141	0	-3.8493557	1E-15	1.4415419267167138E-15	0
 142	1	2.848053	0.84	0.25153881203904033	1
 143	0	-2.73937	1E-15	1.4415419267167138E-15	0
 144	0	-3.59241557	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 146	1	1.31008816	0.8125	0.29956028185890782	1
 147	0	-3.43885779	1E-15	1.4415419267167138E-15	0
 148	0	-0.152019978	0.4	0.73696560849809378	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.618639	0.84	0.25153881203904033	1
 156	0	-3.41809654	1E-15	1.4415419267167138E-15	0
 157	0	-3.33547568	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	9.536341	1	0	1
 160	1	6.860572	1	0	1
 161	0	-2.5829134	1E-15	1.4415419267167138E-15	0
 162	0	-3.09483147	1E-15	1.4415419267167138E-15	0
 163	0	-2.50633955	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 165	0	-2.245256	1E-15	1.4415419267167138E-15	0
 166	1	6.456311	1	0	1
 167	1	4.319108	0.9756098	0.035623875334191583	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.8359299	0.7777778	2.1699250874336404	1
 233	1	3.89948845	0.9411765	0.087462835875881578	1
 234	0	-1.06992626	0.0625	0.093109404391481479	0
-235	0				
+235	0				0
 236	1	8.428113	1	0	1
 237	1	5.33226967	1	0	1
 238	1	9.183852	1	0	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.645902	1	0	1
 247	1	2.597087	0.84	0.25153881203904033	1
 248	0	-1.497818	0.0625	0.093109404391481479	0
-249	0				
+249	0				0
 250	0	-3.67503667	1E-15	1.4415419267167138E-15	0
 251	1	5.0781126	1	0	1
 252	0	3.308917	0.84	2.643855953298599	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	2.38956165	0.84	0.25153881203904033	1
 273	1	0.3306446	0.7777778	0.36257005481575838	1
 274	0	-2.82355762	1E-15	1.4415419267167138E-15	0
-275	0				
+275	0				0
 276	0	-3.35177135	1E-15	1.4415419267167138E-15	0
 277	0	-3.83305979	1E-15	1.4415419267167138E-15	0
 278	0	-3.57612	1E-15	1.4415419267167138E-15	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	6.52714539	1	0	1
 290	0	-4.08999968	1E-15	1.4415419267167138E-15	0
 291	0	-3.57612	1E-15	1.4415419267167138E-15	0
-292	1				
+292	1				0
 293	1	3.63595963	0.9411765	0.087462835875881578	1
-294	0				
+294	0				0
 295	1	5.25647163	1	0	1
 296	0	1.97336864	0.8125	2.4150374992788439	1
-297	0				
+297	0				0
 298	0	-2.03882861	1E-15	1.4415419267167138E-15	0
 299	1	4.99616432	1	0	1
 300	1	5.63767242	1	0	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.14314938	0.84	0.25153881203904033	1
 313	0	-4.08999968	1E-15	1.4415419267167138E-15	0
 314	0	-3.88960457	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 316	1	3.149722	0.84	0.25153881203904033	1
 317	1	7.02619457	1	0	1
 318	0	-3.406486	1E-15	1.4415419267167138E-15	0
 319	0	1.82393885	0.8125	2.4150374992788439	1
 320	1	5.15885925	1	0	1
-321	0				
+321	0				0
 322	0	-3.09483147	1E-15	1.4415419267167138E-15	0
 323	1	3.22143555	0.84	0.25153881203904033	1
 324	0	-3.57612	1E-15	1.4415419267167138E-15	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-2.29045367	1E-15	1.4415419267167138E-15	0
 409	0	-3.13383579	1E-15	1.4415419267167138E-15	0
 410	0	-3.83305979	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	6.52325153	1	0	1
 413	0	-2.39560747	1E-15	1.4415419267167138E-15	0
 414	1	5.304202	1	0	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-3.64896035	1E-15	1.4415419267167138E-15	0
 615	0	-2.675256	1E-15	1.4415419267167138E-15	0
 616	0	-3.35177135	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-3.11112714	1E-15	1.4415419267167138E-15	0
 619	0	-2.870483	1E-15	1.4415419267167138E-15	0
 620	0	-3.35177135	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt
index 69424d1f96..8822aa3d2f 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	4.309107	0.982883155	0.024908174987257281	1
 21	1	6.161626	0.997486651	0.0036305605660221312	1
 22	0	-3.35177135	0.0190011337	0.027676625763894382	0
-23	1				
+23	1				0
 24	0	-3.57612	0.0150948567	0.021943310344814629	0
 25	1	1.68778992	0.7883411	0.34310809466132391	1
 26	0	-3.21128821	0.02193545	0.031998411900987428	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.20465565	0.154014841	0.24129573984468006	0
 38	1	4.3035	0.98278445	0.025053063812451211	1
 39	1	2.444232	0.8913242	0.16597778265246793	1
-40	0				
+40	0				0
 41	1	2.349327	0.881352544	0.18220887767190111	1
 42	1	6.69547653	0.99855864	0.002080942285094773	1
 43	1	0.1725626	0.43382585	1.2048120730945795	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-3.11112714	0.0242936034	0.035481008429150813	0
 137	0	-3.60871148	0.0145974671	0.021214914966477344	0
 138	0	-2.89319158	0.0303093083	0.044403459692558656	0
-139	0				
+139	0				0
 140	0	-3.60871148	0.0145974671	0.021214914966477344	0
 141	0	-3.8493557	0.01139268	0.016530506138550251	0
 142	1	2.848053	0.9259271	0.11102947905485054	1
 143	0	-2.73937	0.0353999846	0.051997261707361145	0
 144	0	-3.59241557	0.0148441121	0.021576064827714625	0
-145	0				
+145	0				0
 146	1	1.31008816	0.7152061	0.48356908051152397	1
 147	0	-3.43885779	0.01737916	0.025293256640113757	0
 148	0	-0.152019978	0.353206038	0.62862188502856431	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.618639	0.9077395	0.139649725798073	1
 156	0	-3.41809654	0.0177530367	0.025842292400220613	0
 157	0	-3.33547568	0.01932072	0.028146699492868216	0
-158	0				
+158	0				0
 159	1	9.536341	0.999925554	0.0001074071635410925	1
 160	1	6.860572	0.998786449	0.0017518465781146784	1
 161	0	-2.5829134	0.0414183028	0.061026700952795158	0
 162	0	-3.09483147	0.0246999636	0.036081984337152172	0
 163	0	-2.50633955	0.04470976	0.065988970965053517	0
-164	0				
+164	0				0
 165	0	-2.245256	0.0579013154	0.086049905177797967	0
 166	1	6.456311	0.998150766	0.0026703506849678977	1
 167	1	4.319108	0.983057857	0.024651767929287045	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.8359299	0.6049175	1.3397742465159499	1
 233	1	3.89948845	0.9739913	0.038019246409892023	1
 234	0	-1.06992626	0.17323719	0.27445460033191865	0
-235	0				
+235	0				0
 236	1	8.428113	0.99976337	0.0003414259594434771	1
 237	1	5.33226967	0.994048536	0.0086117997569089607	1
 238	1	9.183852	0.9998925	0.00015513669190214178	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.645902	0.9998115	0.00027201620468366962	1
 247	1	2.597087	0.9058386	0.14267406349976108	1
 248	0	-1.497818	0.118221387	0.1815116096306757	0
-249	0				
+249	0				0
 250	0	-3.67503667	0.0136346063	0.019805910679898876	0
 251	1	5.0781126	0.9922549	0.011217294571842519	1
 252	0	3.308917	0.952875	4.4073641261174119	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	2.38956165	0.8856733	0.17515349285073656	1
 273	1	0.3306446	0.474698573	1.0749163809587898	1
 274	0	-2.82355762	0.0325194858	0.047695490325124906	0
-275	0				
+275	0				0
 276	0	-3.35177135	0.0190011337	0.027676625763894382	0
 277	0	-3.83305979	0.0115858121	0.016812375308683684	0
 278	0	-3.57612	0.0150948567	0.021943310344814629	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	6.52714539	0.9982823	0.0024802287545360943	1
 290	0	-4.08999968	0.008885143	0.012875839136462838	0
 291	0	-3.57612	0.0150948567	0.021943310344814629	0
-292	1				
+292	1				0
 293	1	3.63595963	0.9660381	0.049847993866089353	1
-294	0				
+294	0				0
 295	1	5.25647163	0.9935618	0.0093183820918222807	1
 296	0	1.97336864	0.8338234	2.589210701355853	1
-297	0				
+297	0				0
 298	0	-2.03882861	0.0708337	0.10599126176574966	0
 299	1	4.99616432	0.9915693	0.012214518276517204	1
 300	1	5.63767242	0.995665669	0.0062667080268442431	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.14314938	0.856945038	0.22272541817603111	1
 313	0	-4.08999968	0.008885143	0.012875839136462838	0
 314	0	-3.88960457	0.0109292	0.015854298528928425	0
-315	0				
+315	0				0
 316	1	3.149722	0.9448283	0.081875960094708669	1
 317	1	7.02619457	0.9989789	0.0014738699989607148	1
 318	0	-3.406486	0.0179655552	0.026154467003641695	0
 319	0	1.82393885	0.8110785	2.4041411141982105	1
 320	1	5.15885925	0.992876351	0.01031403381058839	1
-321	0				
+321	0				0
 322	0	-3.09483147	0.0246999636	0.036081984337152172	0
 323	1	3.22143555	0.948601961	0.076125243844936963	1
 324	0	-3.57612	0.0150948567	0.021943310344814629	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-2.29045367	0.05538148	0.082196274856991033	0
 409	0	-3.13383579	0.0237381756	0.034659977772739645	0
 410	0	-3.83305979	0.0115858121	0.016812375308683684	0
-411	0				
+411	0				0
 412	1	6.52325153	0.99827534	0.0024903070861691909	1
 413	0	-2.39560747	0.0499131419	0.073868682437534181	0
 414	1	5.304202	0.9938727	0.0088670155127870496	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-3.64896035	0.0140054561	0.020348431589167357	0
 615	0	-2.675256	0.0377570055	0.055526832252899339	0
 616	0	-3.35177135	0.0190011337	0.027676625763894382	0
-617	0				
+617	0				0
 618	0	-3.11112714	0.0242936034	0.035481008429150813	0
 619	0	-2.870483	0.0310136	0.045451678527033197	0
 620	0	-3.35177135	0.0190011337	0.027676625763894382	0
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt
index 0f08e7f566..29fbed5bf7 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Assigned
 20	1	4.309107	1
 21	1	6.161626	1
 22	0	-3.35177135	0
-23	1		
+23	1		0
 24	0	-3.57612	0
 25	1	1.68778992	1
 26	0	-3.21128821	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Assigned
 37	0	-1.20465565	0
 38	1	4.3035	1
 39	1	2.444232	1
-40	0		
+40	0		0
 41	1	2.349327	1
 42	1	6.69547653	1
 43	1	0.1725626	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Assigned
 136	0	-3.11112714	0
 137	0	-3.60871148	0
 138	0	-2.89319158	0
-139	0		
+139	0		0
 140	0	-3.60871148	0
 141	0	-3.8493557	0
 142	1	2.848053	1
 143	0	-2.73937	0
 144	0	-3.59241557	0
-145	0		
+145	0		0
 146	1	1.31008816	1
 147	0	-3.43885779	0
 148	0	-0.152019978	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Assigned
 155	1	2.618639	1
 156	0	-3.41809654	0
 157	0	-3.33547568	0
-158	0		
+158	0		0
 159	1	9.536341	1
 160	1	6.860572	1
 161	0	-2.5829134	0
 162	0	-3.09483147	0
 163	0	-2.50633955	0
-164	0		
+164	0		0
 165	0	-2.245256	0
 166	1	6.456311	1
 167	1	4.319108	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Assigned
 232	0	0.8359299	1
 233	1	3.89948845	1
 234	0	-1.06992626	0
-235	0		
+235	0		0
 236	1	8.428113	1
 237	1	5.33226967	1
 238	1	9.183852	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Assigned
 246	1	8.645902	1
 247	1	2.597087	1
 248	0	-1.497818	0
-249	0		
+249	0		0
 250	0	-3.67503667	0
 251	1	5.0781126	1
 252	0	3.308917	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Assigned
 272	1	2.38956165	1
 273	1	0.3306446	1
 274	0	-2.82355762	0
-275	0		
+275	0		0
 276	0	-3.35177135	0
 277	0	-3.83305979	0
 278	0	-3.57612	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Assigned
 289	1	6.52714539	1
 290	0	-4.08999968	0
 291	0	-3.57612	0
-292	1		
+292	1		0
 293	1	3.63595963	1
-294	0		
+294	0		0
 295	1	5.25647163	1
 296	0	1.97336864	1
-297	0		
+297	0		0
 298	0	-2.03882861	0
 299	1	4.99616432	1
 300	1	5.63767242	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Assigned
 312	1	2.14314938	1
 313	0	-4.08999968	0
 314	0	-3.88960457	0
-315	0		
+315	0		0
 316	1	3.149722	1
 317	1	7.02619457	1
 318	0	-3.406486	0
 319	0	1.82393885	1
 320	1	5.15885925	1
-321	0		
+321	0		0
 322	0	-3.09483147	0
 323	1	3.22143555	1
 324	0	-3.57612	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Assigned
 408	0	-2.29045367	0
 409	0	-3.13383579	0
 410	0	-3.83305979	0
-411	0		
+411	0		0
 412	1	6.52325153	1
 413	0	-2.39560747	0
 414	1	5.304202	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Assigned
 614	0	-3.64896035	0
 615	0	-2.675256	0
 616	0	-3.35177135	0
-617	0		
+617	0		0
 618	0	-3.11112714	0
 619	0	-2.870483	0
 620	0	-3.35177135	0
diff --git a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt
index f1da00a926..4aafe56872 100644
--- a/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	2.27614474	0.99046284	0.01382524609823586	1
 21	1	2.71551442	0.9964734	0.0050968413754289565	1
 22	0	-1.91610467	0.007339344	0.010627482294138626	0
-23	1				
+23	1				0
 24	0	-2.12083673	0.00461633364	0.0066753814217522627	0
 25	1	0.579404354	0.6851912	0.54542144241146051	1
 26	0	-1.88108075	0.007944072	0.011506638331166432	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.9763708	0.0591678135	0.087990678318914578	0
 38	1	1.97923112	0.9814142	0.027065950749429996	1
 39	1	0.8320954	0.794680536	0.33155308613045453	1
-40	0				
+40	0				0
 41	1	0.88030076	0.812019646	0.30041346219868831	1
 42	1	3.29876113	0.9990636	0.0013515566126819322	1
 43	1	0.21289444	0.485705882	1.0418451361573347	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.76776826	0.010259659	0.014878012048023576	0
 137	0	-2.00804472	0.00596073642	0.0086252569347725905	0
 138	0	-1.64871967	0.0134130223	0.019481850015569589	0
-139	0				
+139	0				0
 140	0	-2.00804472	0.00596073642	0.0086252569347725905	0
 141	0	-2.15638113	0.00425880356	0.0061572754121802442	0
 142	1	1.42587113	0.93738085	0.093292772480968233	1
 143	0	-1.57122457	0.0159614533	0.023213265078036949	0
 144	0	-2.06444073	0.005245867	0.007588107121760313	0
-145	0				
+145	0				0
 146	1	0.5954063	0.693000734	0.52907121478369279	1
 147	0	-1.97373641	0.00644216966	0.0093241524569279595	0
 148	0	-0.5180371	0.15157719	0.23714468564136862	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	1.38289	0.931381464	0.10255592440494538	1
 156	0	-2.00303721	0.00602870947	0.0087239127220832425	0
 157	0	-1.97250068	0.00646021264	0.0093503519898618208	0
-158	0				
+158	0				0
 159	1	4.52930737	0.9999432	8.1952060728897203E-05	1
 160	1	3.334266	0.9991363	0.0012465526889135054	1
 161	0	-1.5841018	0.015507183	0.022547414886151074	0
 162	0	-1.82416427	0.009033906	0.01309239897866022	0
 163	0	-1.37575865	0.0246935654	0.03607251996647886	0
-164	0				
+164	0				0
 165	0	-1.40072858	0.0233600326	0.034101275741716536	0
 166	1	3.14331079	0.9986662	0.0019255122730899305	1
 167	1	2.61804938	0.995600462	0.0063611951559849299	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.262052536	0.5136946	1.0400654369740645	1
 233	1	2.16407657	0.987723053	0.017821513393369265	1
 234	0	-1.00943446	0.0551115535	0.081784080061402753	0
-235	0				
+235	0				0
 236	1	4.29103756	0.999902248	0.00014103266690546063	1
 237	1	2.42226958	0.9931447	0.0099241759578403005	1
 238	1	4.649124	0.9999568	6.2345058017421014E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	4.143937	0.9998633	0.00019719158494834585	1
 247	1	1.19717526	0.898898065	0.15377057127992425	1
 248	0	-1.217197	0.03506021	0.051489167959956395	0
-249	0				
+249	0				0
 250	0	-2.09497738	0.004895074	0.0070794400974987601	0
 251	1	2.700413	0.9963504	0.0052748803033137396	1
 252	0	1.58717227	0.955785036	4.4993214783146023	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.980280161	0.8443483	0.2440898311411345	1
 273	1	0.00625777245	0.3710024	1.4304995524008379	1
 274	0	-1.73243809	0.0111099789	0.01611801356385726	0
-275	0				
+275	0				0
 276	0	-1.91610467	0.007339344	0.010627482294138626	0
 277	0	-2.21277714	0.00374727719	0.0054163328257276827	0
 278	0	-2.12083673	0.00461633364	0.0066753814217522627	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	3.0956676	0.9985136	0.002146047033326764	1
 290	0	-2.30471754	0.00304132653	0.0043943924919565489	0
 291	0	-2.12083673	0.00461633364	0.0066753814217522627	0
-292	1				
+292	1				0
 293	1	1.9506762	0.980189741	0.028867048302480647	1
-294	0				
+294	0				0
 295	1	2.57708764	0.995172262	0.0069818201865888847	1
 296	0	0.6443205	0.7161847	1.8169756066019795	1
-297	0				
+297	0				0
 298	0	-1.00866961	0.0552023575	0.081922729978655878	0
 299	1	2.32091022	0.9913795	0.012490669010981763	1
 300	1	2.40809751	0.992921352	0.010248646031556275	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	1.19807649	0.899084449	0.15347146394878203	1
 313	0	-2.30471754	0.00304132653	0.0043943924919565489	0
 314	0	-2.26844478	0.00330244377	0.0047723037303054865	0
-315	0				
+315	0				0
 316	1	1.47730184	0.943915665	0.083270128208594502	1
 317	1	3.18132329	0.998776734	0.0017658802629188005	1
 318	0	-1.9538343	0.00673895236	0.0097551599741469968	0
 319	0	0.68000555	0.732414246	1.9019267823886503	1
 320	1	2.448116	0.993534148	0.009358541174187586	1
-321	0				
+321	0				0
 322	0	-1.82416427	0.009033906	0.01309239897866022	0
 323	1	1.739836	0.9683619	0.046381755881038968	1
 324	0	-2.12083673	0.00461633364	0.0066753814217522627	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-1.41561711	0.022598628	0.032976965091470092	0
 409	0	-1.79705584	0.009603847	0.013922383925987339	0
 410	0	-2.21277714	0.00374727719	0.0054163328257276827	0
-411	0				
+411	0				0
 412	1	3.177976	0.9987674	0.0017793974994358322	1
 413	0	-1.40844309	0.0229624342	0.033514061939899156	0
 414	1	2.38908362	0.992610335	0.010700618410080708	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-2.1201086	0.00462396163	0.0066864373761273176	0
 615	0	-1.529671	0.01751844	0.025497765300806271	0
 616	0	-1.91610467	0.007339344	0.010627482294138626	0
-617	0				
+617	0				0
 618	0	-1.76776826	0.010259659	0.014878012048023576	0
 619	0	-1.61943209	0.0143251875	0.020816334525491278	0
 620	0	-1.91610467	0.007339344	0.010627482294138626	0
diff --git a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt
index b337fd78da..d1bbf5dfc5 100644
--- a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	1.25826859	1	0	1
 35	0	-1.41764426	1E-15	1.4415419267167138E-15	0
 37	0	-0.835641861	1E-15	1.4415419267167138E-15	0
-40	0				
+40	0				0
 41	1	0.227130175	0.8666667	0.20645086423799175	1
 44	1	1.61423349	1	0	1
 45	0	-1.47288513	1E-15	1.4415419267167138E-15	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.19960022	1E-15	1.4415419267167138E-15	0
 141	0	-1.47188914	1E-15	1.4415419267167138E-15	0
 144	0	-1.41764426	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 147	0	-1.334388	1E-15	1.4415419267167138E-15	0
 150	0	-1.48176765	1E-15	1.4415419267167138E-15	0
 151	1	0.7797704	1	0	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-1.54539037	1E-15	1.4415419267167138E-15	0
 156	0	-1.35846376	1E-15	1.4415419267167138E-15	0
 161	0	-1.1599288	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 167	1	1.07981849	1	0	1
 169	0	-1.5413084	1E-15	1.4415419267167138E-15	0
 171	0	-1.43690062	1E-15	1.4415419267167138E-15	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.368261	1	0	1
 247	1	0.4837153	0.8666667	0.20645086423799175	1
 248	0	-0.934056163	1E-15	1.4415419267167138E-15	0
-249	0				
+249	0				0
 250	0	-1.41270852	1E-15	1.4415419267167138E-15	0
 252	0	0.706041336	0.8666667	2.9068906815998465	1
 254	1	1.600352	1	0	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.43690062	1E-15	1.4415419267167138E-15	0
 271	0	-1.1428957	1E-15	1.4415419267167138E-15	0
 272	1	0.435359716	0.8666667	0.20645086423799175	1
-275	0				
+275	0				0
 276	0	-1.34414315	1E-15	1.4415419267167138E-15	0
 277	0	-1.49114561	1E-15	1.4415419267167138E-15	0
 278	0	-1.43690062	1E-15	1.4415419267167138E-15	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.43690062	1E-15	1.4415419267167138E-15	0
 293	1	0.9331081	1	0	1
 296	0	0.221757889	0.8666667	2.9068906815998465	1
-297	0				
+297	0				0
 299	1	1.13769388	1	0	1
 300	1	1.24829745	1	0	1
 301	0	-1.43690062	1E-15	1.4415419267167138E-15	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.7455783	0.9151356	0.12794252993534275	1
 317	1	1.81665158	1	0	1
 319	0	0.285441637	0.8666667	2.9068906815998465	1
-321	0				
+321	0				0
 323	1	0.8990345	1	0	1
 327	0	-1.49114561	1E-15	1.4415419267167138E-15	0
 328	1	0.8467562	1	0	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	2.95104	1	0	1
 613	0	-1.29436374	1E-15	1.4415419267167138E-15	0
 614	0	-1.4625113	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-1.2706418	1E-15	1.4415419267167138E-15	0
 619	0	-1.19714069	1E-15	1.4415419267167138E-15	0
 621	0	-0.3866408	0.5799383	1.2513268180432666	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.13828516	1E-15	1.4415419267167138E-15	0
 19	0	-0.9969288	1E-15	1.4415419267167138E-15	0
 22	0	-1.259604	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-1.35031986	1E-15	1.4415419267167138E-15	0
 26	0	-1.22985053	1E-15	1.4415419267167138E-15	0
 27	0	-1.11824775	1E-15	1.4415419267167138E-15	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.22317672	1E-15	1.4415419267167138E-15	0
 135	0	-0.8295188	1E-15	1.4415419267167138E-15	0
 136	0	-1.18892586	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-1.3102448	1E-15	1.4415419267167138E-15	0
 142	1	0.6019325	0.875	0.19264507794239591	1
 143	0	-1.00445139	1E-15	1.4415419267167138E-15	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.01599169	1E-15	1.4415419267167138E-15	0
 155	1	0.7134235	0.875	0.19264507794239591	1
 157	0	-1.27964163	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	2.42447567	1	0	1
 160	1	1.81060028	1	0	1
 162	0	-1.20896339	1E-15	1.4415419267167138E-15	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1.72919893	1	0	1
 232	0	-0.038654685	0.6923077	1.7004398041324202	0
 234	0	-0.661043048	1E-15	1.4415419267167138E-15	0
-235	0				
+235	0				0
 236	1	2.13174057	1	0	1
 238	1	2.40485334	1	0	1
 243	0	-0.8018886	1E-15	1.4415419267167138E-15	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	2.9424572	1	0	1
 287	0	-1.22317672	1E-15	1.4415419267167138E-15	0
 289	1	1.71858239	1	0	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	1.42958808	1	0	1
 298	0	-0.7813908	1E-15	1.4415419267167138E-15	0
 302	1	2.925787	1	0	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.35031986	1E-15	1.4415419267167138E-15	0
 310	0	-1.293855	1E-15	1.4415419267167138E-15	0
 313	0	-1.45160127	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 318	0	-1.24103785	1E-15	1.4415419267167138E-15	0
 320	1	1.18153763	1	0	1
 322	0	-1.20896339	1E-15	1.4415419267167138E-15	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-1.40096045	1E-15	1.4415419267167138E-15	0
 408	0	-0.928058	1E-15	1.4415419267167138E-15	0
 410	0	-1.40096045	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	1.731832	1	0	1
 417	0	-1.40096045	1E-15	1.4415419267167138E-15	0
 420	0	-0.7677182	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt
index fed143de3d..0f9cdffb66 100644
--- a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Assigned
 32	1	1.25826859	1
 35	0	-1.41764426	0
 37	0	-0.835641861	0
-40	0		
+40	0		0
 41	1	0.227130175	1
 44	1	1.61423349	1
 45	0	-1.47288513	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Assigned
 138	0	-1.19960022	0
 141	0	-1.47188914	0
 144	0	-1.41764426	0
-145	0		
+145	0		0
 147	0	-1.334388	0
 150	0	-1.48176765	0
 151	1	0.7797704	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Assigned
 154	0	-1.54539037	0
 156	0	-1.35846376	0
 161	0	-1.1599288	0
-164	0		
+164	0		0
 167	1	1.07981849	1
 169	0	-1.5413084	0
 171	0	-1.43690062	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Assigned
 246	1	2.368261	1
 247	1	0.4837153	1
 248	0	-0.934056163	0
-249	0		
+249	0		0
 250	0	-1.41270852	0
 252	0	0.706041336	1
 254	1	1.600352	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Assigned
 269	0	-1.43690062	0
 271	0	-1.1428957	0
 272	1	0.435359716	1
-275	0		
+275	0		0
 276	0	-1.34414315	0
 277	0	-1.49114561	0
 278	0	-1.43690062	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Assigned
 291	0	-1.43690062	0
 293	1	0.9331081	1
 296	0	0.221757889	1
-297	0		
+297	0		0
 299	1	1.13769388	1
 300	1	1.24829745	1
 301	0	-1.43690062	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Assigned
 316	1	0.7455783	1
 317	1	1.81665158	1
 319	0	0.285441637	1
-321	0		
+321	0		0
 323	1	0.8990345	1
 327	0	-1.49114561	0
 328	1	0.8467562	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Assigned
 612	1	2.95104	1
 613	0	-1.29436374	0
 614	0	-1.4625113	0
-617	0		
+617	0		0
 618	0	-1.2706418	0
 619	0	-1.19714069	0
 621	0	-0.3866408	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Assigned
 17	0	-1.13828516	0
 19	0	-0.9969288	0
 22	0	-1.259604	0
-23	1		
+23	1		0
 24	0	-1.35031986	0
 26	0	-1.22985053	0
 27	0	-1.11824775	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Assigned
 134	0	-1.22317672	0
 135	0	-0.8295188	0
 136	0	-1.18892586	0
-139	0		
+139	0		0
 140	0	-1.3102448	0
 142	1	0.6019325	1
 143	0	-1.00445139	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Assigned
 153	0	-1.01599169	0
 155	1	0.7134235	1
 157	0	-1.27964163	0
-158	0		
+158	0		0
 159	1	2.42447567	1
 160	1	1.81060028	1
 162	0	-1.20896339	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Assigned
 231	1	1.72919893	1
 232	0	-0.038654685	0
 234	0	-0.661043048	0
-235	0		
+235	0		0
 236	1	2.13174057	1
 238	1	2.40485334	1
 243	0	-0.8018886	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Assigned
 286	1	2.9424572	1
 287	0	-1.22317672	0
 289	1	1.71858239	1
-292	1		
-294	0		
+292	1		0
+294	0		0
 295	1	1.42958808	1
 298	0	-0.7813908	0
 302	1	2.925787	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Assigned
 307	0	-1.35031986	0
 310	0	-1.293855	0
 313	0	-1.45160127	0
-315	0		
+315	0		0
 318	0	-1.24103785	0
 320	1	1.18153763	1
 322	0	-1.20896339	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Assigned
 407	0	-1.40096045	0
 408	0	-0.928058	0
 410	0	-1.40096045	0
-411	0		
+411	0		0
 412	1	1.731832	1
 417	0	-1.40096045	0
 420	0	-0.7677182	0
diff --git a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt
index 9c673bc10a..b3c0e5b1d8 100644
--- a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.133441	1	0	1
 21	1	1.46698761	1	0	1
 22	0	-1.29266214	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-1.38898408	1E-15	1.4415419267167138E-15	0
 25	1	0.2072978	0.8125	0.29956028185890782	1
 26	0	-1.27053475	1E-15	1.4415419267167138E-15	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.7899848	1E-15	1.4415419267167138E-15	0
 38	1	1.07285547	0.955555558	0.065588337627980248	1
 39	1	0.444084644	0.826086938	0.27563447429444238	1
-40	0				
+40	0				0
 41	1	0.278235674	0.8125	0.29956028185890782	1
 42	1	1.82501435	1	0	1
 43	1	0.0648527145	0.8125	0.29956028185890782	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.21864986	1E-15	1.4415419267167138E-15	0
 137	0	-1.34436476	1E-15	1.4415419267167138E-15	0
 138	0	-1.15066063	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-1.34436476	1E-15	1.4415419267167138E-15	0
 141	0	-1.418377	1E-15	1.4415419267167138E-15	0
 142	1	0.605928659	0.826086938	0.27563447429444238	1
 143	0	-1.04888356	1E-15	1.4415419267167138E-15	0
 144	0	-1.36667442	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 146	1	0.263422	0.8125	0.29956028185890782	1
 147	0	-1.28818154	1E-15	1.4415419267167138E-15	0
 148	0	-0.38141644	0.333333343	0.5849625222189877	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.7075844	0.826086938	0.27563447429444238	1
 156	0	-1.30894148	1E-15	1.4415419267167138E-15	0
 157	0	-1.3149718	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	2.41813564	1	0	1
 160	1	1.80749393	1	0	1
 161	0	-1.10798192	1E-15	1.4415419267167138E-15	0
 162	0	-1.24095953	1E-15	1.4415419267167138E-15	0
 163	0	-1.14838839	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 165	0	-0.9971055	1E-15	1.4415419267167138E-15	0
 166	1	1.77878284	1	0	1
 167	1	1.0986836	0.955555558	0.065588337627980248	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.0348134041	0.727272749	1.8744692325712462	0
 233	1	1.102045	1	0	1
 234	0	-0.709003	0.1	0.15200309583369792	0
-235	0				
+235	0				0
 236	1	2.13387632	1	0	1
 237	1	1.230866	1	0	1
 238	1	2.40226221	1	0	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.38478136	1	0	1
 247	1	0.5292797	0.826086938	0.27563447429444238	1
 248	0	-0.8721206	1E-15	1.4415419267167138E-15	0
-249	0				
+249	0				0
 250	0	-1.3606441	1E-15	1.4415419267167138E-15	0
 251	1	1.35184932	1	0	1
 252	0	0.7461872	0.826086938	2.5235618055722013	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.451641083	0.826086938	0.27563447429444238	1
 273	1	-0.184997916	0.727272749	0.45943157564163517	0
 274	0	-1.1819942	1E-15	1.4415419267167138E-15	0
-275	0				
+275	0				0
 276	0	-1.29266214	1E-15	1.4415419267167138E-15	0
 277	0	-1.4406867	1E-15	1.4415419267167138E-15	0
 278	0	-1.38898408	1E-15	1.4415419267167138E-15	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.698751	1	0	1
 290	0	-1.49238932	1E-15	1.4415419267167138E-15	0
 291	0	-1.38898408	1E-15	1.4415419267167138E-15	0
-292	1				
+292	1				0
 293	1	0.9705	0.955555558	0.065588337627980248	1
-294	0				
+294	0				0
 295	1	1.44576406	1	0	1
 296	0	0.264410973	0.8125	2.4150374992788439	1
-297	0				
+297	0				0
 298	0	-0.785661459	1E-15	1.4415419267167138E-15	0
 299	1	1.16638494	1	0	1
 300	1	1.27287531	1	0	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.6419792	0.826086938	0.27563447429444238	1
 313	0	-1.49238932	1E-15	1.4415419267167138E-15	0
 314	0	-1.4823153	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 316	1	0.773257732	0.826086938	0.27563447429444238	1
 317	1	1.83582067	1	0	1
 318	0	-1.26409817	1E-15	1.4415419267167138E-15	0
 319	0	0.303462982	0.8125	2.4150374992788439	1
 320	1	1.16069293	1	0	1
-321	0				
+321	0				0
 322	0	-1.24095953	1E-15	1.4415419267167138E-15	0
 323	1	0.909108639	0.955555558	0.065588337627980248	1
 324	0	-1.38898408	1E-15	1.4415419267167138E-15	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-0.9617897	1E-15	1.4415419267167138E-15	0
 409	0	-1.22467291	1E-15	1.4415419267167138E-15	0
 410	0	-1.4406867	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	1.77363062	1	0	1
 413	0	-1.02494574	1E-15	1.4415419267167138E-15	0
 414	1	1.26032782	1	0	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.408303	1E-15	1.4415419267167138E-15	0
 615	0	-1.0826714	1E-15	1.4415419267167138E-15	0
 616	0	-1.29266214	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-1.21864986	1E-15	1.4415419267167138E-15	0
 619	0	-1.14463758	1E-15	1.4415419267167138E-15	0
 620	0	-1.29266214	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt
index c5e41e5240..c72088d43c 100644
--- a/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleDebug/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Assigned
 20	1	1.133441	1
 21	1	1.46698761	1
 22	0	-1.29266214	0
-23	1		
+23	1		0
 24	0	-1.38898408	0
 25	1	0.2072978	1
 26	0	-1.27053475	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Assigned
 37	0	-0.7899848	0
 38	1	1.07285547	1
 39	1	0.444084644	1
-40	0		
+40	0		0
 41	1	0.278235674	1
 42	1	1.82501435	1
 43	1	0.0648527145	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Assigned
 136	0	-1.21864986	0
 137	0	-1.34436476	0
 138	0	-1.15066063	0
-139	0		
+139	0		0
 140	0	-1.34436476	0
 141	0	-1.418377	0
 142	1	0.605928659	1
 143	0	-1.04888356	0
 144	0	-1.36667442	0
-145	0		
+145	0		0
 146	1	0.263422	1
 147	0	-1.28818154	0
 148	0	-0.38141644	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Assigned
 155	1	0.7075844	1
 156	0	-1.30894148	0
 157	0	-1.3149718	0
-158	0		
+158	0		0
 159	1	2.41813564	1
 160	1	1.80749393	1
 161	0	-1.10798192	0
 162	0	-1.24095953	0
 163	0	-1.14838839	0
-164	0		
+164	0		0
 165	0	-0.9971055	0
 166	1	1.77878284	1
 167	1	1.0986836	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Assigned
 232	0	-0.0348134041	0
 233	1	1.102045	1
 234	0	-0.709003	0
-235	0		
+235	0		0
 236	1	2.13387632	1
 237	1	1.230866	1
 238	1	2.40226221	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Assigned
 246	1	2.38478136	1
 247	1	0.5292797	1
 248	0	-0.8721206	0
-249	0		
+249	0		0
 250	0	-1.3606441	0
 251	1	1.35184932	1
 252	0	0.7461872	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Assigned
 272	1	0.451641083	1
 273	1	-0.184997916	0
 274	0	-1.1819942	0
-275	0		
+275	0		0
 276	0	-1.29266214	0
 277	0	-1.4406867	0
 278	0	-1.38898408	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Assigned
 289	1	1.698751	1
 290	0	-1.49238932	0
 291	0	-1.38898408	0
-292	1		
+292	1		0
 293	1	0.9705	1
-294	0		
+294	0		0
 295	1	1.44576406	1
 296	0	0.264410973	1
-297	0		
+297	0		0
 298	0	-0.785661459	0
 299	1	1.16638494	1
 300	1	1.27287531	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Assigned
 312	1	0.6419792	1
 313	0	-1.49238932	0
 314	0	-1.4823153	0
-315	0		
+315	0		0
 316	1	0.773257732	1
 317	1	1.83582067	1
 318	0	-1.26409817	0
 319	0	0.303462982	1
 320	1	1.16069293	1
-321	0		
+321	0		0
 322	0	-1.24095953	0
 323	1	0.909108639	1
 324	0	-1.38898408	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Assigned
 408	0	-0.9617897	0
 409	0	-1.22467291	0
 410	0	-1.4406867	0
-411	0		
+411	0		0
 412	1	1.77363062	1
 413	0	-1.02494574	0
 414	1	1.26032782	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Assigned
 614	0	-1.408303	0
 615	0	-1.0826714	0
 616	0	-1.29266214	0
-617	0		
+617	0		0
 618	0	-1.21864986	0
 619	0	-1.14463758	0
 620	0	-1.29266214	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.txt
index 55744d3dbb..05d8592b8a 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	7.01161575	0.999099433	0.0012998283148002473	1
 35	0	-5.546275	0.0038867984	0.0056183906346792553	0
 37	0	-0.627175331	0.3481513	0.61739094617065504	0
-40	0				
+40	0				0
 41	1	3.0365572	0.9541986	0.067638527006529184	1
 44	1	6.61341858	0.998659551	0.0019351561965343684	1
 45	0	-5.565003	0.00381495967	0.0055143486004666058	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.72209072	0.008818108	0.012778263407408707	0
 141	0	-6.18090439	0.002064286	0.0029812133205916491	0
 144	0	-5.546275	0.0038867984	0.0056183906346792553	0
-145	0				
+145	0				0
 147	0	-5.305633	0.0049390397	0.0071431828757896592	0
 150	0	-5.43029261	0.004362697	0.0063078105710409225	0
 151	1	4.990402	0.993243039	0.0097813179599174817	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.58201027	0.00138314639	0.0019968397134892645	0
 156	0	-5.6663394	0.00344857574	0.0049838416366178697	0
 161	0	-3.992939	0.0181113519	0.026368671070599831	0
-164	0				
+164	0				0
 167	1	6.79999542	0.9988875	0.0016059215653949079	1
 169	0	-6.41288567	0.00163759827	0.0023644914709276374	0
 171	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	10.4554977	0.9999712	4.1534408054175585E-05	1
 247	1	2.7647686	0.940742	0.088128954823708028	1
 248	0	-3.52696	0.0285547972	0.041795476162409473	0
-249	0				
+249	0				0
 250	0	-6.30096865	0.00183116761	0.0026442381917314273	0
 252	0	4.46767044	0.988656163	6.4619475094968903	1
 254	1	5.268241	0.994873762	0.007414618780919654	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.312752	0.004904177	0.007092637921430613	0
 271	0	-3.70832729	0.02393173	0.034946036680259647	0
 272	1	3.75608158	0.9771588	0.033335080773514915	1
-275	0				
+275	0				0
 276	0	-5.145169	0.005793728	0.0083828901690503332	0
 277	0	-5.947381	0.002605866	0.0037643767357215252	0
 278	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.312752	0.004904177	0.007092637921430613	0
 293	1	4.889887	0.992533863	0.0108117709104356	1
 296	0	1.11456966	0.752980053	2.0173005524167049	1
-297	0				
+297	0				0
 299	1	7.92421341	0.999638259	0.00052197576964742038	1
 300	1	5.01128674	0.993381739	0.009579868932513079	1
 301	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.64061546	0.974434555	0.037362801100438832	1
 317	1	8.889477	0.9998622	0.00019882564438936136	1
 319	0	2.932189	0.9494149	4.3051439460642333	1
-321	0				
+321	0				0
 323	1	5.11123276	0.994007468	0.0086714037349760222	1
 327	0	-5.947381	0.002605866	0.0037643767357215252	0
 328	1	3.24846554	0.962617934	0.054964793658751787	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	16.72465	0.99999994	8.5991327994145617E-08	1
 613	0	-5.02813625	0.00650837226	0.0094202851039732072	0
 614	0	-5.6638155	0.00345726055	0.0049964145907412149	0
-617	0				
+617	0				0
 618	0	-4.744063	0.008628122	0.012501759455550775	0
 619	0	-4.34295654	0.01283126	0.01863138517568386	0
 621	0	0.373829842	0.5923841	1.2947177664921086	1
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.23449326	0.0142802689	0.020750590335179415	0
 19	0	-3.10273981	0.04299438	0.063400697943788428	0
 22	0	-5.130806	0.00587705	0.0085038042327941973	0
-23	1				
+23	1				0
 24	0	-5.932124	0.002645822	0.0038221729188529165	0
 26	0	-5.0699935	0.006243238	0.0090353231046563232	0
 27	0	-3.99905157	0.01800297	0.026209433910245255	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.12534046	0.00590906851	0.0085502708566916	0
 135	0	-2.97098112	0.0487542	0.072109916649189282	0
 136	0	-4.56492853	0.0103033585	0.014941712057931327	0
-139	0				
+139	0				0
 140	0	-5.461241	0.00423030974	0.0061159922992663762	0
 142	1	3.05590534	0.9550368	0.066371741280747978	1
 143	0	-5.35564375	0.004699242	0.0067955523991724961	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.276688	0.0136983329	0.019899122722508662	0
 155	1	1.77740765	0.8553765	0.22536855303918271	1
 157	0	-5.366247	0.004649908	0.0067240441834850199	0
-158	0				
+158	0				0
 159	1	8.96132851	0.999871731	0.0001850652016644095	1
 160	1	6.856139	0.998948157	0.001518287560141836	1
 162	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.663686	0.9965423	0.0049970870434534837	1
 232	0	0.928171158	0.71670413	1.8196185260804569	1
 234	0	-3.391735	0.0325547643	0.047748098148187916	0
-235	0				
+235	0				0
 236	1	7.88262749	0.9996229	0.00054416973071506056	1
 238	1	8.651073	0.9998251	0.00025232061237670696	1
 243	0	-4.03390265	0.0173970815	0.025319570708974903	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.9212322	0.99998194	2.6055606891255495E-05	1
 287	0	-5.12534046	0.00590906851	0.0085502708566916	0
 289	1	5.185871	0.9944361	0.0080494462952667781	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77450371	0.9916284	0.012128492162908918	1
 298	0	-2.54918242	0.07248143	0.10855193009256793	0
 302	1	11.1919193	0.999986231	1.9864132926342996E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.932124	0.002645822	0.0038221729188529165	0
 310	0	-5.691217	0.00336412713	0.0048615916252809817	0
 313	0	-6.59299469	0.0013680571	0.0019750404849533288	0
-315	0				
+315	0				0
 318	0	-5.91572762	0.00268944423	0.0038852748092412133	0
 320	1	4.1229	0.9840607	0.023180779648038535	1
 322	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 408	0	-4.386099	0.0122961234	0.017849522550602435	0
 410	0	-6.26255941	0.00190273311	0.0027476785076986981	0
-411	0				
+411	0				0
 412	1	7.037607	0.99912256	0.0012664339928697493	1
 417	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 420	0	-3.338777	0.0342646	0.050300135586962377	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt
index 0a4ce514a2..44c3149a1c 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	7.01161575	0.999099433	0.0012998283148002473	1
 35	0	-5.546275	0.0038867984	0.0056183906346792553	0
 37	0	-0.627175331	0.3481513	0.61739094617065504	0
-40	0				
+40	0				0
 41	1	3.0365572	0.9541986	0.067638527006529184	1
 44	1	6.61341858	0.998659551	0.0019351561965343684	1
 45	0	-5.565003	0.00381495967	0.0055143486004666058	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.72209072	0.008818108	0.012778263407408707	0
 141	0	-6.18090439	0.002064286	0.0029812133205916491	0
 144	0	-5.546275	0.0038867984	0.0056183906346792553	0
-145	0				
+145	0				0
 147	0	-5.305633	0.0049390397	0.0071431828757896592	0
 150	0	-5.43029261	0.004362697	0.0063078105710409225	0
 151	1	4.990402	0.993243039	0.0097813179599174817	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.58201027	0.00138314639	0.0019968397134892645	0
 156	0	-5.6663394	0.00344857574	0.0049838416366178697	0
 161	0	-3.992939	0.0181113519	0.026368671070599831	0
-164	0				
+164	0				0
 167	1	6.79999542	0.9988875	0.0016059215653949079	1
 169	0	-6.41288567	0.00163759827	0.0023644914709276374	0
 171	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	10.4554977	0.9999712	4.1534408054175585E-05	1
 247	1	2.7647686	0.940742	0.088128954823708028	0
 248	0	-3.52696	0.0285547972	0.041795476162409473	0
-249	0				
+249	0				0
 250	0	-6.30096865	0.00183116761	0.0026442381917314273	0
 252	0	4.46767044	0.988656163	6.4619475094968903	1
 254	1	5.268241	0.994873762	0.007414618780919654	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.312752	0.004904177	0.007092637921430613	0
 271	0	-3.70832729	0.02393173	0.034946036680259647	0
 272	1	3.75608158	0.9771588	0.033335080773514915	1
-275	0				
+275	0				0
 276	0	-5.145169	0.005793728	0.0083828901690503332	0
 277	0	-5.947381	0.002605866	0.0037643767357215252	0
 278	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.312752	0.004904177	0.007092637921430613	0
 293	1	4.889887	0.992533863	0.0108117709104356	1
 296	0	1.11456966	0.752980053	2.0173005524167049	0
-297	0				
+297	0				0
 299	1	7.92421341	0.999638259	0.00052197576964742038	1
 300	1	5.01128674	0.993381739	0.009579868932513079	1
 301	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.64061546	0.974434555	0.037362801100438832	1
 317	1	8.889477	0.9998622	0.00019882564438936136	1
 319	0	2.932189	0.9494149	4.3051439460642333	0
-321	0				
+321	0				0
 323	1	5.11123276	0.994007468	0.0086714037349760222	1
 327	0	-5.947381	0.002605866	0.0037643767357215252	0
 328	1	3.24846554	0.962617934	0.054964793658751787	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	16.72465	0.99999994	8.5991327994145617E-08	1
 613	0	-5.02813625	0.00650837226	0.0094202851039732072	0
 614	0	-5.6638155	0.00345726055	0.0049964145907412149	0
-617	0				
+617	0				0
 618	0	-4.744063	0.008628122	0.012501759455550775	0
 619	0	-4.34295654	0.01283126	0.01863138517568386	0
 621	0	0.373829842	0.5923841	1.2947177664921086	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.23449326	0.0142802689	0.020750590335179415	0
 19	0	-3.10273981	0.04299438	0.063400697943788428	0
 22	0	-5.130806	0.00587705	0.0085038042327941973	0
-23	1				
+23	1				0
 24	0	-5.932124	0.002645822	0.0038221729188529165	0
 26	0	-5.0699935	0.006243238	0.0090353231046563232	0
 27	0	-3.99905157	0.01800297	0.026209433910245255	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.12534046	0.00590906851	0.0085502708566916	0
 135	0	-2.97098112	0.0487542	0.072109916649189282	0
 136	0	-4.56492853	0.0103033585	0.014941712057931327	0
-139	0				
+139	0				0
 140	0	-5.461241	0.00423030974	0.0061159922992663762	0
 142	1	3.05590534	0.9550368	0.066371741280747978	1
 143	0	-5.35564375	0.004699242	0.0067955523991724961	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.276688	0.0136983329	0.019899122722508662	0
 155	1	1.77740765	0.8553765	0.22536855303918271	0
 157	0	-5.366247	0.004649908	0.0067240441834850199	0
-158	0				
+158	0				0
 159	1	8.96132851	0.999871731	0.0001850652016644095	1
 160	1	6.856139	0.998948157	0.001518287560141836	1
 162	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.663686	0.9965423	0.0049970870434534837	1
 232	0	0.928171158	0.71670413	1.8196185260804569	0
 234	0	-3.391735	0.0325547643	0.047748098148187916	0
-235	0				
+235	0				0
 236	1	7.88262749	0.9996229	0.00054416973071506056	1
 238	1	8.651073	0.9998251	0.00025232061237670696	1
 243	0	-4.03390265	0.0173970815	0.025319570708974903	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.9212322	0.99998194	2.6055606891255495E-05	1
 287	0	-5.12534046	0.00590906851	0.0085502708566916	0
 289	1	5.185871	0.9944361	0.0080494462952667781	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77450371	0.9916284	0.012128492162908918	1
 298	0	-2.54918242	0.07248143	0.10855193009256793	0
 302	1	11.1919193	0.999986231	1.9864132926342996E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.932124	0.002645822	0.0038221729188529165	0
 310	0	-5.691217	0.00336412713	0.0048615916252809817	0
 313	0	-6.59299469	0.0013680571	0.0019750404849533288	0
-315	0				
+315	0				0
 318	0	-5.91572762	0.00268944423	0.0038852748092412133	0
 320	1	4.1229	0.9840607	0.023180779648038535	1
 322	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 408	0	-4.386099	0.0122961234	0.017849522550602435	0
 410	0	-6.26255941	0.00190273311	0.0027476785076986981	0
-411	0				
+411	0				0
 412	1	7.037607	0.99912256	0.0012664339928697493	1
 417	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 420	0	-3.338777	0.0342646	0.050300135586962377	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt
index 2748bad72f..b1d74e635f 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	5.917115	0.9973143	0.003879895635620469	1
 35	0	-5.023262	0.006539965	0.0094661631818091386	0
 37	0	-1.38112783	0.200827926	0.3234219246434899	0
-40	0				
+40	0				0
 41	1	1.99977684	0.880773664	0.18315676412764836	1
 44	1	6.1460495	0.997862637	0.0030868629883528767	1
 45	0	-4.92853165	0.00718512246	0.010403360173725132	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.17745543	0.0151058007	0.021959341229968121	0
 141	0	-5.50801945	0.00403775927	0.0058370475132605874	0
 144	0	-5.023262	0.006539965	0.0094661631818091386	0
-145	0				
+145	0				0
 147	0	-4.81479263	0.00804367848	0.011651498579728541	0
 150	0	-4.92451668	0.00721382024	0.01044506254471955	0
 151	1	4.048602	0.9828524	0.024953319944645107	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-5.80309772	0.00300910859	0.0043477707884351756	0
 156	0	-4.933721	0.00714819832	0.010349705365439381	0
 161	0	-3.81854677	0.0214878246	0.031338292831631254	0
-164	0				
+164	0				0
 167	1	7.07203674	0.999152243	0.0012235733412714462	1
 169	0	-5.652446	0.00349665456	0.0050534464360921993	0
 171	0	-4.83358335	0.007895125	0.011435459622816726	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.218597	0.9999008	0.00014309666195095306	1
 247	1	1.9463377	0.87504673	0.19256803177214576	1
 248	0	-3.2993412	0.0355937965	0.052287163877458576	0
-249	0				
+249	0				0
 250	0	-5.418478	0.004414317	0.006382611353481173	0
 252	0	3.48067	0.970132768	5.0652926577610451	1
 254	1	4.863985	0.9923395	0.011094325676462969	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-4.83358335	0.007895125	0.011435459622816726	0
 271	0	-3.65327024	0.0252520833	0.036898928715096181	0
 272	1	3.02218533	0.9535664	0.068594734962942897	1
-275	0				
+275	0				0
 276	0	-4.72818375	0.008765012	0.012700983189760973	0
 277	0	-5.3183403	0.00487697963	0.00705320751084503	0
 278	0	-4.83358335	0.007895125	0.011435459622816726	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-4.83358335	0.007895125	0.011435459622816726	0
 293	1	3.6722765	0.975211561	0.036212866280089365	1
 296	0	0.9506779	0.7212515	1.8429639897619017	1
-297	0				
+297	0				0
 299	1	5.993658	0.9975117	0.0035943536619517991	1
 300	1	5.41301346	0.9955616	0.0064175103553020287	1
 301	0	-4.83358335	0.007895125	0.011435459622816726	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	2.857479	0.945704	0.080539421519246923	1
 317	1	7.483817	0.9994382	0.00081069597738820146	1
 319	0	2.14308548	0.895020843	3.2518251711052208	1
-321	0				
+321	0				0
 323	1	4.38443756	0.987683654	0.017879061305842645	1
 327	0	-5.3183403	0.00487697963	0.00705320751084503	0
 328	1	1.9153614	0.8716203	0.19822830198625993	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	15.0148582	0.9999997	4.2995669122556443E-07	1
 613	0	-4.76532364	0.008448151	0.012239880753341762	0
 614	0	-5.114196	0.005974896	0.00864580721752186	0
-617	0				
+617	0				0
 618	0	-4.43310547	0.0117381271	0.017034712310540854	0
 619	0	-4.138027	0.0157037526	0.022835500585175472	0
 621	0	-0.147964478	0.463076234	0.89721082981393785	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.094967	0.0163834114	0.023832028779250634	0
 19	0	-3.158533	0.0407563634	0.06003080556474015	0
 22	0	-4.786547	0.008272208	0.011983909171361835	0
-23	1				
+23	1				0
 24	0	-5.49961758	0.00407168828	0.0058861960152521283	0
 26	0	-4.637971	0.009584561	0.013894290826829943	0
 27	0	-3.85011339	0.02083403	0.030374676365783088	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-4.786547	0.008272208	0.011983909171361835	0
 135	0	-2.91646814	0.0513454638	0.07604528657651706	0
 136	0	-4.31833	0.01314697	0.019092852440504127	0
-139	0				
+139	0				0
 140	0	-5.00991058	0.006627286	0.009592975357514695	0
 142	1	2.566639	0.9286834	0.10674124733849408	1
 143	0	-4.68576	0.009141385	0.013248879501449318	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-3.91140127	0.0196197983	0.028586744893093978	0
 155	1	1.73489761	0.8500378	0.23440107518588552	1
 157	0	-5.03140068	0.00648729829	0.0093896829482070059	0
-158	0				
+158	0				0
 159	1	8.209714	0.9997281	0.00039234577165867646	1
 160	1	6.214038	0.9980028	0.0028841924162386562	1
 162	0	-4.563184	0.0103211654	0.014967669647872791	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.128908	0.994111836	0.0085199331359509835	1
 232	0	0.387944221	0.5957877	1.3068148861794051	1
 234	0	-3.05071926	0.04518643	0.066709024779774861	0
-235	0				
+235	0				0
 236	1	7.45407867	0.999421239	0.00083521748895634131	1
 238	1	8.351737	0.9997641	0.00034039381967173406	1
 243	0	-3.79230738	0.02204652	0.032162254419967784	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.2351351	0.9999641	5.1767706679585828E-05	1
 287	0	-4.786547	0.008272208	0.011983909171361835	0
 289	1	5.007719	0.993358254	0.0096139756423385195	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.08445454	0.9834463	0.024081816959951673	1
 298	0	-2.520249	0.07445079	0.11161839829444895	0
 302	1	10.2925406	0.999966145	4.8843899665517181E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.49961758	0.00407168828	0.0058861960152521283	0
 310	0	-5.254764	0.00519544445	0.0075149807235167431	0
 313	0	-5.94634438	0.00260856142	0.0037682756571934027	0
-315	0				
+315	0				0
 318	0	-5.49961758	0.00407168828	0.0058861960152521283	0
 320	1	3.84560966	0.9790739	0.030510363432469476	1
 322	0	-4.563184	0.0103211654	0.014967669647872791	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-5.722981	0.003259291	0.00470984242704696	0
 408	0	-3.98740244	0.0182100739	0.026513731287650329	0
 410	0	-5.722981	0.003259291	0.00470984242704696	0
-411	0				
+411	0				0
 412	1	5.972435	0.997458458	0.0036713375244963246	1
 417	0	-5.722981	0.003259291	0.00470984242704696	0
 420	0	-3.14838743	0.0411548652	0.060630273661156198	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt
index c81880f594..aad01de654 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	5.678712	0.9965937	0.0049226209615764287	1
 21	1	6.001464	0.997531	0.0035664232425213858	1
 22	0	-5.02218437	0.00654697046	0.009476336418019371	0
-23	1				
+23	1				0
 24	0	-5.557753	0.00384261133	0.0055543948499928858	0
 25	1	0.7356682	0.676047862	0.56480270753052697	1
 26	0	-5.01491547	0.006594418	0.0095452416271748757	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.86437464	0.134193972	0.20788424941725006	0
 38	1	4.26738262	0.986175358	0.020083890425044392	1
 39	1	0.948868752	0.7208876	0.47215375855428471	1
-40	0				
+40	0				0
 41	1	2.21941185	0.9019792	0.14883391736209772	1
 42	1	6.171118	0.997915447	0.00301051350343931	1
 43	1	-0.406847954	0.399668157	1.3231254618912542	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.573848	0.0102128033	0.014809714349895977	0
 137	0	-5.38329029	0.00457168929	0.0066106759896893642	0
 138	0	-4.32377768	0.0130764758	0.018989799023276886	0
-139	0				
+139	0				0
 140	0	-5.38329029	0.00457168929	0.0066106759896893642	0
 141	0	-5.83162737	0.00292472052	0.0042256622529479159	0
 142	1	3.1618576	0.9593734	0.059835633747694031	1
 143	0	-4.83655453	0.007871887	0.011401667353256314	0
 144	0	-5.470522	0.004191393	0.00605960993587892	0
-145	0				
+145	0				0
 146	1	0.0557060242	0.5139229	0.96037607240274647	1
 147	0	-5.47995234	0.00415221555	0.0060028519951750492	0
 148	0	-1.59599066	0.168542728	0.26628596824729922	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.20912266	0.901065767	0.15029568586304221	1
 156	0	-5.58346558	0.003745433	0.0054136621278108544	0
 157	0	-5.109416	0.006003351	0.0086871066895572498	0
-158	0				
+158	0				0
 159	1	9.879018	0.99994874	7.3954435339176224E-05	1
 160	1	6.966673	0.9990581	0.0013594752512588889	1
 161	0	-4.01959	0.0176434461	0.025681337989317106	0
 162	0	-4.661079	0.009367671	0.01357839101244592	0
 163	0	-3.39304066	0.03251367	0.04768681882905737	0
-164	0				
+164	0				0
 165	0	-3.65873766	0.0251178537	0.036700273114887771	0
 166	1	6.106388	0.9977764	0.0032115643460085509	1
 167	1	6.96164227	0.999053359	0.0013663610592643267	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.434880257	0.607038438	1.3475398955993996	1
 233	1	4.62145329	0.9902574	0.014124543390739288	1
 234	0	-3.19655	0.0392957628	0.057835744186683809	0
-235	0				
+235	0				0
 236	1	9.488486	0.9999243	0.00010921311695177715	1
 237	1	5.185233	0.994432569	0.0080545481788837064	1
 238	1	10.3383093	0.999967635	4.6694045347237877E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.706185	0.9998345	0.00023881767606976273	1
 247	1	1.85991	0.865286469	0.20875025156266316	1
 248	0	-3.24698353	0.03743543	0.055044774760243595	0
-249	0				
+249	0				0
 250	0	-5.9445715	0.00261317822	0.0037749537255417041	0
 251	1	6.851535	0.998943269	0.001525346290754842	1
 252	0	3.15871048	0.959250569	4.6170762873605469	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.54124355	0.8236454	0.27990471757503477	1
 273	1	-0.485281944	0.381005645	1.3921157227274092	0
 274	0	-4.467927	0.0113409776	0.016455057773140165	0
-275	0				
+275	0				0
 276	0	-5.02218437	0.00654697046	0.009476336418019371	0
 277	0	-5.918859	0.00268105837	0.0038731439944547637	0
 278	0	-5.557753	0.00384261133	0.0055543948499928858	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	6.391654	0.9983273	0.0024151950596217639	1
 290	0	-6.27996445	0.00186996383	0.0027003130775063206	0
 291	0	-5.557753	0.00384261133	0.0055543948499928858	0
-292	1				
+292	1				0
 293	1	4.062559	0.98308605	0.024610393646554929	1
-294	0				
+294	0				0
 295	1	5.48979473	0.9958883	0.0059441683338054239	1
 296	0	0.7984762	0.689648449	1.6880247409542737	1
-297	0				
+297	0				0
 298	0	-2.82211971	0.05614051	0.083355987427050499	0
 299	1	5.92269325	0.9973292	0.0038583400725341575	1
 300	1	5.553643	0.9961416	0.0055772429838620297	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.505681	0.924539149	0.11319368429557292	1
 313	0	-6.27996445	0.00186996383	0.0027003130775063206	0
 314	0	-5.996913	0.00248024915	0.0035826879721537609	0
-315	0				
+315	0				0
 316	1	2.06765842	0.8877198	0.17182370265537225	1
 317	1	6.799261	0.998886645	0.0016071267852858751	1
 318	0	-5.323591	0.004851562	0.0070163583406618974	0
 319	0	1.16352749	0.7619731	2.0708033667370818	1
 320	1	5.47767448	0.995838344	0.006016528395062894	1
-321	0				
+321	0				0
 322	0	-4.661079	0.009367671	0.01357839101244592	0
 323	1	3.7019043	0.975917757	0.035168522105486828	1
 324	0	-5.557753	0.00384261133	0.0055543948499928858	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.06660128	0.0168468487	0.024511924018010906	0
 409	0	-4.77211475	0.008391453	0.012157388278315496	0
 410	0	-5.918859	0.00268105837	0.0038731439944547637	0
-411	0				
+411	0				0
 412	1	6.93106556	0.999024	0.0014087955764285343	1
 413	0	-3.5143342	0.02890712	0.042318806680098388	0
 414	1	4.808298	0.9919043	0.0117271336749766	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-5.548576	0.00387790077	0.0056055040477979955	0
 615	0	-4.073707	0.0167295579	0.024339819893712551	0
 616	0	-5.02218437	0.00654697046	0.009476336418019371	0
-617	0				
+617	0				0
 618	0	-4.573848	0.0102128033	0.014809714349895977	0
 619	0	-4.12551069	0.0158983991	0.023120824431946189	0
 620	0	-5.02218437	0.00654697046	0.009476336418019371	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt
index 4789a49c72..a31588d1b9 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	7.041827	0.999126256	0.0012610978584151201	1
 21	1	7.16006565	0.9992236	0.0011205580676841706	1
 22	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-23	1				
+23	1				0
 24	0	-6.16573143	0.00209578	0.003026744365055557	0
 25	1	1.140585	0.757787049	0.4001356116356401	1
 26	0	-5.39192247	0.00453257374	0.006553986122637143	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.74917936	0.148150727	0.23132991391158644	0
 38	1	5.25044537	0.9947822	0.0075473881419006704	1
 39	1	1.14784718	0.7591175	0.39760491464649406	1
-40	0				
+40	0				0
 41	1	2.83779049	0.9446841	0.082096136496848479	1
 42	1	5.84602737	0.997117	0.0041653216557672994	1
 43	1	-0.115566254	0.471140563	1.0857705467412089	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.81180668	0.008067538	0.011686200181083801	0
 137	0	-5.771742	0.003104659	0.0044860436134326774	0
 138	0	-4.708121	0.008941052	0.01295722303877558	0
-139	0				
+139	0				0
 140	0	-5.771742	0.003104659	0.0044860436134326774	0
 141	0	-6.35020638	0.00174334215	0.0025173059685722476	0
 142	1	3.59143162	0.9731803	0.039220987499558525	1
 143	0	-5.32383156	0.00485040154	0.0070146760362167319	0
 144	0	-5.96873665	0.00255094632	0.0036849396417204128	0
-145	0				
+145	0				0
 146	1	-0.228344917	0.443160534	1.1740986883981319	0
 147	0	-6.02899933	0.00240211817	0.0034696929544304877	0
 148	0	-1.17236042	0.236428589	0.38916500660996345	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.561039	0.928311646	0.10731887720885433	1
 156	0	-6.32817459	0.0017821081	0.0025733321754180501	0
 157	0	-5.587267	0.00373127544	0.0053931605303660906	0
-158	0				
+158	0				0
 159	1	9.957122	0.9999526	6.836472348564471E-05	1
 160	1	7.81574535	0.999596834	0.00058176260649806227	1
 161	0	-4.194911	0.0148482891	0.02158218175164682	0
 162	0	-5.008802	0.00663458835	0.0096035809636014526	0
 163	0	-4.450941	0.0115330191	0.016735320470494343	0
-164	0				
+164	0				0
 165	0	-3.79370117	0.022016488	0.0321179521831969	0
 166	1	6.78795338	0.998874	0.0016253773809814112	1
 167	1	6.650817	0.9987087	0.0018641198790525675	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.440856934	0.6084632	1.3527802863415537	1
 233	1	5.59169	0.996285141	0.0053693888063565016	1
 234	0	-3.380312	0.0329164639	0.048287580681296273	0
-235	0				
+235	0				0
 236	1	9.42349148	0.9999192	0.00011660894974341421	1
 237	1	5.527053	0.9960381	0.005727196256675989	1
 238	1	10.3295126	0.999967337	4.7124015954602722E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.522981	0.999926865	0.00010551521477366078	1
 247	1	2.22113419	0.9021314	0.14859054441592434	1
 248	0	-3.25320721	0.037211813	0.0547096542674552	0
-249	0				
+249	0				0
 250	0	-6.70964432	0.00121761323	0.0017577148937104486	0
 251	1	8.275113	0.9997453	0.00036748773339945429	1
 252	0	3.75820923	0.97720623	5.4552166396980901	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.25216866	0.777675033	0.36276067331990891	1
 273	1	-0.4770708	0.382944047	1.3847944817499098	0
 274	0	-4.773376	0.008380964	0.01214212852075712	0
-275	0				
+275	0				0
 276	0	-5.39027166	0.00454002852	0.0065647900946516503	0
 277	0	-6.547201	0.00143207016	0.0020675212884715419	0
 278	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	7.07017231	0.999150634	0.0012258970788924348	1
 290	0	-6.928671	0.0009783435	0.0014121422633917285	0
 291	0	-6.16573143	0.00209578	0.003026744365055557	0
-292	1				
+292	1				0
 293	1	5.206727	0.9945503	0.0078837745923848179	1
-294	0				
+294	0				0
 295	1	6.0751133	0.9977059	0.0033135223937081622	1
 296	0	1.04628563	0.740061	1.9437549070362801	1
-297	0				
+297	0				0
 298	0	-2.41310167	0.08217907	0.12371538777024385	0
 299	1	7.396323	0.999386847	0.00088486407096525718	1
 300	1	5.69218445	0.996639132	0.0048568731086720204	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	3.90498447	0.9802564	0.02876897031816629	1
 313	0	-6.928671	0.0009783435	0.0014121422633917285	0
 314	0	-6.664193	0.00127416	0.0018393963949252371	0
-315	0				
+315	0				0
 316	1	2.20020485	0.9002679	0.15157371666802275	1
 317	1	7.75578	0.9995719	0.00061772192605728435	1
 318	0	-5.81475639	0.002974334	0.0042974510254079716	0
 319	0	1.38163567	0.7992536	2.3165538563686012	1
 320	1	5.837037	0.997091	0.0042029227668842466	1
-321	0				
+321	0				0
 322	0	-5.008802	0.00663458835	0.0096035809636014526	0
 323	1	4.26100159	0.9860881	0.020211552173447847	1
 324	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.4899044	0.0110971872	0.016099351806882618	0
 409	0	-5.286586	0.00503353868	0.0072801992795113032	0
 410	0	-6.547201	0.00143207016	0.0020675212884715419	0
-411	0				
+411	0				0
 412	1	7.575248	0.9994873	0.00073988707471124668	1
 413	0	-3.748186	0.0230181254	0.033596298028071243	0
 414	1	5.274519	0.994905651	0.0073683771133106393	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.085728	0.00226994278	0.0032785576690230068	0
 615	0	-4.604435	0.0099082	0.01436579907268937	0
 616	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-617	0				
+617	0				0
 618	0	-4.81180668	0.008067538	0.011686200181083801	0
 619	0	-4.233342	0.0142964814	0.020774319020048612	0
 620	0	-5.39027166	0.00454002852	0.0065647900946516503	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt
index 92afd941f0..105627b7fb 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	7.041827	0.999126256	0.0012610978584151201	1
 21	1	7.16006565	0.9992236	0.0011205580676841706	1
 22	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-23	1				
+23	1				0
 24	0	-6.16573143	0.00209578	0.003026744365055557	0
 25	1	1.140585	0.757787049	0.4001356116356401	0
 26	0	-5.39192247	0.00453257374	0.006553986122637143	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.74917936	0.148150727	0.23132991391158644	0
 38	1	5.25044537	0.9947822	0.0075473881419006704	1
 39	1	1.14784718	0.7591175	0.39760491464649406	0
-40	0				
+40	0				0
 41	1	2.83779049	0.9446841	0.082096136496848479	0
 42	1	5.84602737	0.997117	0.0041653216557672994	1
 43	1	-0.115566254	0.471140563	1.0857705467412089	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.81180668	0.008067538	0.011686200181083801	0
 137	0	-5.771742	0.003104659	0.0044860436134326774	0
 138	0	-4.708121	0.008941052	0.01295722303877558	0
-139	0				
+139	0				0
 140	0	-5.771742	0.003104659	0.0044860436134326774	0
 141	0	-6.35020638	0.00174334215	0.0025173059685722476	0
 142	1	3.59143162	0.9731803	0.039220987499558525	1
 143	0	-5.32383156	0.00485040154	0.0070146760362167319	0
 144	0	-5.96873665	0.00255094632	0.0036849396417204128	0
-145	0				
+145	0				0
 146	1	-0.228344917	0.443160534	1.1740986883981319	0
 147	0	-6.02899933	0.00240211817	0.0034696929544304877	0
 148	0	-1.17236042	0.236428589	0.38916500660996345	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.561039	0.928311646	0.10731887720885433	0
 156	0	-6.32817459	0.0017821081	0.0025733321754180501	0
 157	0	-5.587267	0.00373127544	0.0053931605303660906	0
-158	0				
+158	0				0
 159	1	9.957122	0.9999526	6.836472348564471E-05	1
 160	1	7.81574535	0.999596834	0.00058176260649806227	1
 161	0	-4.194911	0.0148482891	0.02158218175164682	0
 162	0	-5.008802	0.00663458835	0.0096035809636014526	0
 163	0	-4.450941	0.0115330191	0.016735320470494343	0
-164	0				
+164	0				0
 165	0	-3.79370117	0.022016488	0.0321179521831969	0
 166	1	6.78795338	0.998874	0.0016253773809814112	1
 167	1	6.650817	0.9987087	0.0018641198790525675	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.440856934	0.6084632	1.3527802863415537	0
 233	1	5.59169	0.996285141	0.0053693888063565016	1
 234	0	-3.380312	0.0329164639	0.048287580681296273	0
-235	0				
+235	0				0
 236	1	9.42349148	0.9999192	0.00011660894974341421	1
 237	1	5.527053	0.9960381	0.005727196256675989	1
 238	1	10.3295126	0.999967337	4.7124015954602722E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.522981	0.999926865	0.00010551521477366078	1
 247	1	2.22113419	0.9021314	0.14859054441592434	0
 248	0	-3.25320721	0.037211813	0.0547096542674552	0
-249	0				
+249	0				0
 250	0	-6.70964432	0.00121761323	0.0017577148937104486	0
 251	1	8.275113	0.9997453	0.00036748773339945429	1
 252	0	3.75820923	0.97720623	5.4552166396980901	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.25216866	0.777675033	0.36276067331990891	0
 273	1	-0.4770708	0.382944047	1.3847944817499098	0
 274	0	-4.773376	0.008380964	0.01214212852075712	0
-275	0				
+275	0				0
 276	0	-5.39027166	0.00454002852	0.0065647900946516503	0
 277	0	-6.547201	0.00143207016	0.0020675212884715419	0
 278	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	7.07017231	0.999150634	0.0012258970788924348	1
 290	0	-6.928671	0.0009783435	0.0014121422633917285	0
 291	0	-6.16573143	0.00209578	0.003026744365055557	0
-292	1				
+292	1				0
 293	1	5.206727	0.9945503	0.0078837745923848179	1
-294	0				
+294	0				0
 295	1	6.0751133	0.9977059	0.0033135223937081622	1
 296	0	1.04628563	0.740061	1.9437549070362801	0
-297	0				
+297	0				0
 298	0	-2.41310167	0.08217907	0.12371538777024385	0
 299	1	7.396323	0.999386847	0.00088486407096525718	1
 300	1	5.69218445	0.996639132	0.0048568731086720204	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	3.90498447	0.9802564	0.02876897031816629	1
 313	0	-6.928671	0.0009783435	0.0014121422633917285	0
 314	0	-6.664193	0.00127416	0.0018393963949252371	0
-315	0				
+315	0				0
 316	1	2.20020485	0.9002679	0.15157371666802275	0
 317	1	7.75578	0.9995719	0.00061772192605728435	1
 318	0	-5.81475639	0.002974334	0.0042974510254079716	0
 319	0	1.38163567	0.7992536	2.3165538563686012	0
 320	1	5.837037	0.997091	0.0042029227668842466	1
-321	0				
+321	0				0
 322	0	-5.008802	0.00663458835	0.0096035809636014526	0
 323	1	4.26100159	0.9860881	0.020211552173447847	1
 324	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.4899044	0.0110971872	0.016099351806882618	0
 409	0	-5.286586	0.00503353868	0.0072801992795113032	0
 410	0	-6.547201	0.00143207016	0.0020675212884715419	0
-411	0				
+411	0				0
 412	1	7.575248	0.9994873	0.00073988707471124668	1
 413	0	-3.748186	0.0230181254	0.033596298028071243	0
 414	1	5.274519	0.994905651	0.0073683771133106393	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.085728	0.00226994278	0.0032785576690230068	0
 615	0	-4.604435	0.0099082	0.01436579907268937	0
 616	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-617	0				
+617	0				0
 618	0	-4.81180668	0.008067538	0.011686200181083801	0
 619	0	-4.233342	0.0142964814	0.020774319020048612	0
 620	0	-5.39027166	0.00454002852	0.0065647900946516503	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt
index 946584d7cb..199b9a59b7 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	4.455554	0.98851943	0.016658771299360001	1
 35	0	-5.20966339	0.005433825	0.0078607284616035548	0
 37	0	-1.95550251	0.1239546	0.19092245979854006	0
-40	0				
+40	0				0
 41	1	1.363338	0.796301663	0.32861302447496599	1
 44	1	2.93189621	0.949400842	0.074910765340690438	1
 45	0	-5.4227767	0.00439546537	0.0063552935777515963	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.283581	0.01360552	0.019763368834071083	0
 141	0	-5.903559	0.0027222808	0.0039327765009182425	0
 144	0	-5.20966339	0.005433825	0.0078607284616035548	0
-145	0				
+145	0				0
 147	0	-4.808229	0.008096219	0.011727915268260366	0
 150	0	-4.955528	0.00699508563	0.010127237230146099	0
 151	1	2.9794178	0.9516356	0.071518853245330763	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.343319	0.00175536959	0.0025346883174766728	0
 156	0	-4.870145	0.00761383865	0.011026477645071437	0
 161	0	-3.876839	0.0202957559	0.029581804866342248	0
-164	0				
+164	0				0
 167	1	1.63665962	0.8370799	0.25656278900168672	1
 169	0	-6.067718	0.00231109979	0.0033380709957833601	0
 171	0	-4.955528	0.00699508563	0.010127237230146099	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	6.373105	0.9982961	0.0024603307167519865	1
 247	1	1.08481979	0.747405	0.42003789409759523	1
 248	0	-3.67766953	0.0246584155	0.036020526273661445	0
-249	0				
+249	0				0
 250	0	-5.56404066	0.00381861837	0.0055196472135604522	0
 252	0	2.67256546	0.935388267	3.9520600195019679	1
 254	1	2.64337635	0.933601558	0.099121125939627047	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-4.955528	0.00699508563	0.010127237230146099	0
 271	0	-3.63624859	0.0256744642	0.037524217400354012	0
 272	1	2.26432514	0.905879	0.14260970234578763	1
-275	0				
+275	0				0
 276	0	-5.20966339	0.005433825	0.0078607284616035548	0
 277	0	-5.6494236	0.003507201	0.0050687153327134771	0
 278	0	-4.955528	0.00699508563	0.010127237230146099	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-4.955528	0.00699508563	0.010127237230146099	0
 293	1	2.05892181	0.886846	0.17324448166666195	1
 296	0	1.99554062	0.880328059	3.0628431682446857	1
-297	0				
+297	0				0
 299	1	3.69336033	0.9757162	0.035466552037373179	1
 300	1	4.02837372	0.9825081	0.025458759934045509	1
 301	0	-4.955528	0.00699508563	0.010127237230146099	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	2.94207382	0.9498875	0.074171415588786135	1
 317	1	4.312872	0.986782	0.019196674360521217	1
 319	0	2.41989422	0.9183318	3.6140817927103961	1
-321	0				
+321	0				0
 323	1	3.56970787	0.972607434	0.040070476517068486	1
 327	0	-5.6494236	0.003507201	0.0050687153327134771	0
 328	1	1.70264626	0.845880032	0.24147502978012392	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	7.478863	0.9994354	0.00081473984708772015	1
 613	0	-4.91670847	0.00726995664	0.010526641032229434	0
 614	0	-5.20966339	0.005433825	0.0078607284616035548	0
-617	0				
+617	0				0
 618	0	-4.769904	0.008409867	0.01218417928555986	0
 619	0	-4.330144	0.0129945707	0.018870074173474232	0
 621	0	-0.284356117	0.429386139	0.80941330227154873	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-3.99180722	0.0181314889	0.026398258875503611	0
 19	0	-3.49091744	0.0295717642	0.043306566793261343	0
 22	0	-4.74231339	0.008643099	0.012523555687056959	0
-23	1				
+23	1				0
 24	0	-4.99358654	0.00673562335	0.0097503246472711684	0
 26	0	-4.230923	0.01433061	0.020824270758417435	0
 27	0	-3.74053383	0.0231908429	0.0338513700113664	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-4.74265528	0.00864017	0.012519293184591884	0
 135	0	-2.40284228	0.08295622	0.12493748028384198	0
 136	0	-4.24142361	0.0141830426	0.020608297294341209	0
-139	0				
+139	0				0
 140	0	-4.99192953	0.006746718	0.0097664397610658042	0
 142	1	1.883389	0.8679999	0.20423319963131603	1
 143	0	-3.93245554	0.0192188919	0.027996904861385053	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-3.71085787	0.02387269	0.034858773809671437	0
 155	1	2.1317234	0.8939485	0.1617363815870177	1
 157	0	-4.492697	0.0110665858	0.016054708591916572	0
-158	0				
+158	0				0
 159	1	7.019025	0.9991061	0.0012901886373564615	1
 160	1	5.00210667	0.9933211	0.0096679074407147667	1
 162	0	-4.492697	0.0110665858	0.016054708591916572	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	4.06135273	0.983066	0.02463978413547805	1
 232	0	0.582720757	0.641693234	1.4807328100816015	1
 234	0	-2.76217723	0.0594026	0.08835075047841523	0
-235	0				
+235	0				0
 236	1	5.42756176	0.995625436	0.0063250060270779312	1
 238	1	6.00247669	0.9975335	0.0035628026721853763	1
 243	0	-3.18360639	0.039787326	0.058574116415727635	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	7.122633	0.999194	0.0011632435375058345	1
 287	0	-4.74265528	0.00864017	0.012519293184591884	0
 289	1	5.24414349	0.994749367	0.0075950186704868833	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	3.85042763	0.979172349	0.030365276805999493	1
 298	0	-2.97889614	0.0483884327	0.07155528637722855	0
 302	1	7.28154945	0.999312341	0.00099242318488484949	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-4.99358654	0.00673562335	0.0097503246472711684	0
 310	0	-4.74265528	0.00864017	0.012519293184591884	0
 313	0	-5.49281931	0.004099349	0.005926265742136525	0
-315	0				
+315	0				0
 318	0	-4.994271	0.006731047	0.0097436773674529319	0
 320	1	3.98940563	0.9818257	0.026461150371251282	1
 322	0	-4.492697	0.0110665858	0.016054708591916572	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-5.243203	0.00525554	0.0076021355607147146	0
 408	0	-2.50673819	0.07538716	0.11307869372093513	0
 410	0	-5.243203	0.00525554	0.0076021355607147146	0
-411	0				
+411	0				0
 412	1	4.41673565	0.9880704	0.017314215991460075	1
 417	0	-5.243203	0.00525554	0.0076021355607147146	0
 420	0	-2.416037	0.08195794	0.12336783697816152	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt
index fc9c09274b..e1541ef4c5 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	3.60211229	0.973457634	0.038809901663734138	1
 21	1	4.16481066	0.9847049	0.022236640568523543	1
 22	0	-5.531984	0.003942524	0.0056991017626305011	0
-23	1				
+23	1				0
 24	0	-5.641634	0.00353453052	0.0051082826744376919	0
 25	1	1.07475233	0.7454996	0.42372049536525624	1
 26	0	-5.05423546	0.00634177	0.0091783743058498103	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-2.63470244	0.06693815	0.099955373797007113	0
 38	1	3.11990023	0.9577062	0.062344933763709205	1
 39	1	1.3332	0.791369438	0.33757674381727276	1
-40	0				
+40	0				0
 41	1	1.76657629	0.8540314	0.22763900783247884	1
 42	1	5.77468061	0.996904433	0.0044728861234643764	1
 43	1	-0.160024166	0.4600791	1.1200461625954479	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.98228741	0.00681164	0.0098607417433267518	0
 137	0	-5.97203064	0.00254257885	0.0036728371153443573	0
 138	0	-4.3374877	0.0129007176	0.018732896643962105	0
-139	0				
+139	0				0
 140	0	-5.97203064	0.00254257885	0.0036728371153443573	0
 141	0	-5.97203064	0.00254257885	0.0036728371153443573	0
 142	1	3.62155676	0.973955452	0.03807230821683618	1
 143	0	-4.06941748	0.0168002676	0.024443571870852193	0
 144	0	-5.531984	0.003942524	0.0056991017626305011	0
-145	0				
+145	0				0
 146	1	0.845272541	0.69957453	0.51545032982981998	1
 147	0	-5.264244	0.00514667667	0.0074442579843589417	0
 148	0	-3.53539133	0.0283218417	0.041449555087460649	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.63197279	0.9328912	0.1002192761113103	1
 156	0	-4.95913267	0.00697009	0.010090922390098837	0
 157	0	-5.091937	0.006108559	0.0088398149066821179	0
-158	0				
+158	0				0
 159	1	7.637605	0.9995183	0.00069514934090023593	1
 160	1	5.102776	0.9939569	0.00874476585784471	1
 161	0	-4.27338028	0.013743096	0.019964600611336557	0
 162	0	-5.091937	0.006108559	0.0088398149066821179	0
 163	0	-3.67683315	0.0246785376	0.036050290649489301	0
-164	0				
+164	0				0
 165	0	-3.45594358	0.0305921026	0.044824259180207618	0
 166	1	4.88854	0.9925239	0.010826239558709188	1
 167	1	2.59618044	0.930615366	0.10374308707957469	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.465872765	0.6144064	1.3748470144034199	1
 233	1	3.621717	0.9739595	0.038066304453576054	1
 234	0	-3.43166828	0.0313202776	0.045908353174351067	0
-235	0				
+235	0				0
 236	1	6.647678	0.9987047	0.001869974861439897	1
 237	1	4.42246	0.9881377	0.017215962974508822	1
 238	1	6.44672251	0.9984168	0.0022859116128351314	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	6.46864176	0.998451054	0.0022363890442921863	1
 247	1	1.5234189	0.8210414	0.28447311579312373	1
 248	0	-4.00451946	0.0179065578	0.026067797200325149	0
-249	0				
+249	0				0
 250	0	-5.39917946	0.00449994765	0.0065067030783201637	0
 251	1	4.104112	0.983763337	0.023616805142920666	1
 252	0	2.75052214	0.939942837	4.0575198580425882	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.62500715	0.8354845	0.2593150232737797	1
 273	1	0.228233814	0.556812048	0.84473766721050514	1
 274	0	-4.82307673	0.007977848	0.011555758238394069	0
-275	0				
+275	0				0
 276	0	-5.531984	0.003942524	0.0056991017626305011	0
 277	0	-6.0816803	0.00227912888	0.003291840622802274	0
 278	0	-5.641634	0.00353453052	0.0051082826744376919	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	5.68027353	0.996598959	0.004915027880645002	1
 290	0	-6.521727	0.00146896509	0.0021208267355545722	0
 291	0	-5.641634	0.00353453052	0.0051082826744376919	0
-292	1				
+292	1				0
 293	1	2.365685	0.9141729	0.12946106222132911	1
-294	0				
+294	0				0
 295	1	4.049787	0.982872367	0.024924010557578272	1
 296	0	1.7836585	0.856148	2.7973428610745215	1
-297	0				
+297	0				0
 298	0	-3.845192	0.0209346656	0.030522958750931656	0
 299	1	2.974937	0.95142895	0.071832170969213474	1
 300	1	4.1471324	0.9844364	0.022630102350657457	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.437553883	0.607676	0.71862571139451958	1
 313	0	-6.521727	0.00146896509	0.0021208267355545722	0
 314	0	-6.0816803	0.00227912888	0.003291840622802274	0
-315	0				
+315	0				0
 316	1	3.03096247	0.953953445	0.068009233653927595	1
 317	1	3.97896051	0.9816384	0.026736450275361392	1
 318	0	-5.641634	0.00353453052	0.0051082826744376919	0
 319	0	1.61403608	0.833970964	2.5904925250318187	1
 320	1	5.17757845	0.99439	0.0081162910482616441	1
-321	0				
+321	0				0
 322	0	-5.091937	0.006108559	0.0088398149066821179	0
 323	1	3.22697878	0.961837	0.056135679390163992	1
 324	0	-5.641634	0.00353453052	0.0051082826744376919	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-2.996994	0.0475618578	0.070302697725435973	0
 409	0	-4.887184	0.007486166	0.010840883662554117	0
 410	0	-6.0816803	0.00227912888	0.003291840622802274	0
-411	0				
+411	0				0
 412	1	4.5649085	0.989696443	0.014942001227255185	1
 413	0	-3.34774446	0.0339691	0.049858759088118251	0
 414	1	3.84952021	0.9791539	0.030392501392593196	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-5.531984	0.003942524	0.0056991017626305011	0
 615	0	-3.69268847	0.02429977	0.035490127405006046	0
 616	0	-5.531984	0.003942524	0.0056991017626305011	0
-617	0				
+617	0				0
 618	0	-4.98228741	0.00681164	0.0098607417433267518	0
 619	0	-4.43259048	0.0117441025	0.01704343535923129	0
 620	0	-5.531984	0.003942524	0.0056991017626305011	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt
index c637c69d47..92061b497a 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	7.291877	0.999319434	0.00098218321186686951	1
 35	0	-5.869519	0.002816277	0.0040687610645090766	0
 37	0	-1.02334213	0.2643769	0.44296132773823416	0
-40	0				
+40	0				0
 41	1	2.78505516	0.9418629	0.086411051010362436	1
 44	1	7.821086	0.999599	0.00057866567352766714	1
 45	0	-5.776886	0.00308877858	0.0044630618032660361	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.724151	0.008800117	0.01275207813790242	0
 141	0	-6.55827045	0.00141632778	0.0020447774455947432	0
 144	0	-5.869519	0.002816277	0.0040687610645090766	0
-145	0				
+145	0				0
 147	0	-5.710598	0.00329976762	0.0047684300667823433	0
 150	0	-5.60911131	0.003650946	0.0052768404018184306	0
 151	1	5.118675	0.994051635	0.0086073014434059885	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.9242	0.000982723	0.0014184666437026428	0
 156	0	-5.82082272	0.00295639853	0.0042714987401086318	0
 161	0	-4.27493	0.0137221068	0.019933897944770858	0
-164	0				
+164	0				0
 167	1	8.728978	0.9998382	0.00023348534112652949	1
 169	0	-6.667038	0.00127054506	0.0018341745113224558	0
 171	0	-5.546697	0.00388516486	0.0056160247410976614	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	11.3055124	0.9999877	1.7714321792245208E-05	1
 247	1	2.306137	0.909384	0.1370384544406823	1
 248	0	-3.57901382	0.027145749	0.039704412233602736	0
-249	0				
+249	0				0
 250	0	-6.50957441	0.00148689921	0.0021467385111997687	0
 252	0	4.227894	0.9856265	6.1204466632636887	1
 254	1	5.1967	0.9944957	0.0079629764358839714	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.546697	0.00388516486	0.0056160247410976614	0
 271	0	-4.08297968	0.01657771	0.024117038815588843	0
 272	1	4.140359	0.984332263	0.022782712303270784	1
-275	0				
+275	0				0
 276	0	-5.50359	0.004055611	0.0058629065586406487	0
 277	0	-6.235449	0.00195492059	0.002823114622841595	0
 278	0	-5.546697	0.00388516486	0.0056160247410976614	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.546697	0.00388516486	0.0056160247410976614	0
 293	1	4.409566	0.9879857	0.017437977320811163	1
 296	0	1.50613689	0.818488	2.4618631795162846	1
-297	0				
+297	0				0
 299	1	7.93633366	0.9996426	0.00051569614495754321	1
 300	1	7.85100842	0.9996108	0.00056163266102194308	1
 301	0	-5.546697	0.00388516486	0.0056160247410976614	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.280983	0.9637706	0.05323826093940856	1
 317	1	9.331164	0.999911368	0.00012787476790525535	1
 319	0	2.956067	0.9505495	4.3378705942158717	1
-321	0				
+321	0				0
 323	1	5.71478939	0.996714	0.0047485078589307303	1
 327	0	-6.235449	0.00195492059	0.002823114622841595	0
 328	1	1.37423134	0.7980629	0.32542559954710693	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	18.5483551	1	0	1
 613	0	-5.86728668	0.00282255374	0.0040778419569695535	0
 614	0	-5.931934	0.00264632422	0.0038228993852335589	0
-617	0				
+617	0				0
 618	0	-5.1376605	0.00583713735	0.0084458830416492391	0
 619	0	-4.771732	0.00839464	0.012162025043583415	0
 621	0	0.3424616	0.5847883	1.2680810757859888	1
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.595036	0.01000083	0.014500778622910757	0
 19	0	-3.32248163	0.03480794	0.051112046016137037	0
 22	0	-5.58065033	0.00375595246	0.0054288957255828087	0
-23	1				
+23	1				0
 24	0	-6.503868	0.00149539544	0.0021590142749859306	0
 26	0	-5.548387	0.00387863023	0.0056065605311466102	0
 27	0	-4.308096	0.0132804094	0.01928794203033625	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.58065033	0.00375595246	0.0054288957255828087	0
 135	0	-3.21473217	0.038615074	0.056813911931726302	0
 136	0	-4.944373	0.007072995	0.010240432848577178	0
-139	0				
+139	0				0
 140	0	-5.929988	0.00265146513	0.0038303358354253489	0
 142	1	3.36657238	0.966643333	0.048944424422816823	1
 143	0	-5.92445755	0.0026661302	0.0038515494632620751	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.654668	0.009427353	0.013665310686569912	0
 155	1	1.85960007	0.865250349	0.20881047650865889	1
 157	0	-5.867591	0.00282169762	0.0040766033438554457	0
-158	0				
+158	0				0
 159	1	9.591543	0.9999317	9.8549424786689596E-05	1
 160	1	7.363619	0.9993665	0.00091420540184684017	1
 162	0	-5.231313	0.00531806657	0.0076928219174680146	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.973879	0.9974621	0.0036660786976757281	1
 232	0	1.10679436	0.751531	2.008862256839882	1
 234	0	-3.7641573	0.0226616841	0.033070042201646284	0
-235	0				
+235	0				0
 236	1	8.480452	0.9997926	0.00029928085261473974	1
 238	1	9.448584	0.9999212	0.00011368501131740873	1
 243	0	-4.52710867	0.0106962454	0.015514542524251164	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	11.9692574	0.9999937	9.115109290810302E-06	1
 287	0	-5.58065033	0.00375595246	0.0054288957255828087	0
 289	1	5.61943245	0.9963864	0.005222752234881816	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	5.155699	0.9942666	0.008295308421383105	1
 298	0	-2.71633816	0.0620161332	0.092364986128816551	0
 302	1	12.1483784	0.9999947	7.6532482629398447E-06	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-6.503868	0.00149539544	0.0021590142749859306	0
 310	0	-6.216928	0.001991392	0.00287583593610438	0
 313	0	-7.2025423	0.000744136	0.0010739609416730365	0
-315	0				
+315	0				0
 318	0	-6.503868	0.00149539544	0.0021590142749859306	0
 320	1	4.269491	0.9862041	0.02004186218454097	1
 322	0	-5.231313	0.00531806657	0.0076928219174680146	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-6.853205	0.00105495122	0.0015227762658880663	0
 408	0	-4.852546	0.00774797052	0.011221486878031036	0
 410	0	-6.853205	0.00105495122	0.0015227762658880663	0
-411	0				
+411	0				0
 412	1	7.587702	0.9994936	0.00073076734716613276	1
 417	0	-6.853205	0.00105495122	0.0015227762658880663	0
 420	0	-3.639381	0.0255962238	0.037408370576337828	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt
index a0df8ed00a..4ee5047adb 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	6.59719467	0.9986377	0.0019667577188335239	1
 21	1	6.9093914	0.999002635	0.0014396108762453246	1
 22	0	-5.50264263	0.00405943953	0.0058684526611357517	0
-23	1				
+23	1				0
 24	0	-6.14459133	0.002140461	0.0030913421022840675	0
 25	1	0.9981127	0.7306873	0.4526739227114121	1
 26	0	-5.56536674	0.00381357735	0.0055123467049374769	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.79816341	0.142074779	0.22107619020053021	0
 38	1	4.925646	0.9927943	0.010433298358924143	1
 39	1	0.895828247	0.7100915	0.49392321501990555	1
-40	0				
+40	0				0
 41	1	2.72234154	0.93833214	0.091829412491125792	1
 42	1	6.45601654	0.998431444	0.0022647243580549464	1
 43	1	-0.5776577	0.359471738	1.4760497444221736	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.965955	0.006923029	0.010022553277705419	0
 137	0	-5.93407059	0.00264069065	0.0038147503192492542	0
 138	0	-4.668453	0.009299485	0.013479092815885742	0
-139	0				
+139	0				0
 140	0	-5.93407059	0.00264069065	0.0038147503192492542	0
 141	0	-6.47075844	0.00154565845	0.0022316389032971582	0
 142	1	3.64823437	0.9746237	0.037082819238846716	1
 143	0	-5.466771	0.00420707744	0.0060823331671915537	0
 144	0	-6.03933048	0.002377488	0.0034340739321673348	0
-145	0				
+145	0				0
 146	1	-0.110341072	0.4724427	1.0817887726099731	0
 147	0	-6.11751556	0.002199078	0.0031760924132441036	0
 148	0	-1.55709267	0.174064219	0.2758984827724662	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.36491013	0.9141121	0.12955701132443528	1
 156	0	-6.267907	0.00189260417	0.002733037741461919	0
 157	0	-5.607903	0.003655344	0.0052832085489667481	0
-158	0				
+158	0				0
 159	1	10.9176846	0.9999819	2.614159977229895E-05	1
 160	1	7.75989342	0.9995737	0.00061514108379339587	1
 161	0	-4.309515	0.0132618267	0.019260772318565499	0
 162	0	-5.07121468	0.006235666	0.0090243302579491296	0
 163	0	-3.76092339	0.02273342	0.033175939048272665	0
-164	0				
+164	0				0
 165	0	-3.924346	0.0193723515	0.028222656292276067	0
 166	1	6.74228859	0.998821437	0.001701309224545778	1
 167	1	7.94067574	0.99964416	0.0005134595729021004	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.7225275	0.673163354	1.6133583443719168	1
 233	1	5.29774761	0.995022058	0.0071995859979441072	1
 234	0	-3.554101	0.027811477	0.040691992083778071	0
-235	0				
+235	0				0
 236	1	10.4206543	0.9999702	4.2996303413732479E-05	1
 237	1	5.828807	0.997067034	0.0042375925496323883	1
 238	1	11.3587952	0.9999883	1.6854398235588073E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.599171	0.9999322	9.7775450197580527E-05	1
 247	1	2.067935	0.887747347	0.17177895049852415	1
 248	0	-3.4094696	0.0320008248	0.046922276673100262	0
-249	0				
+249	0				0
 250	0	-6.699335	0.0012302153	0.0017759181240158319	0
 251	1	7.9959507	0.9996633	0.00048584679587356108	1
 252	0	3.6111412	0.9736899	5.2482402117884597	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.72366619	0.848600447	0.23684265601696217	1
 273	1	-0.342484474	0.4152061	1.2681004399882052	0
 274	0	-4.846204	0.007796883	0.011292605602753639	0
-275	0				
+275	0				0
 276	0	-5.50264263	0.00405943953	0.0058684526611357517	0
 277	0	-6.57601929	0.0013914461	0.0020088303041534395	0
 278	0	-6.14459133	0.002140461	0.0030913421022840675	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	7.101452	0.999176741	0.0011882013529343118	1
 290	0	-7.007447	0.0009042981	0.0013052166206428517	0
 291	0	-6.14459133	0.002140461	0.0030913421022840675	0
-292	1				
+292	1				0
 293	1	4.6855	0.9908563	0.013252265463070151	1
-294	0				
+294	0				0
 295	1	6.2168417	0.99800843	0.0028760930785605436	1
 296	0	1.02090549	0.735148966	1.9167469555439196	1
-297	0				
+297	0				0
 298	0	-3.02001572	0.0465297773	0.068740211727588499	0
 299	1	7.09773827	0.9991737	0.0011925905306341051	1
 300	1	6.64691544	0.998703659	0.001871438610749495	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.90730953	0.9482066	0.076726654530730437	1
 313	0	-7.007447	0.0009042981	0.0013052166206428517	0
 314	0	-6.649353	0.001293185	0.0018668790298154393	0
-315	0				
+315	0				0
 316	1	2.12067223	0.892896235	0.16343556787762994	1
 317	1	7.5715065	0.9994854	0.00074264021133653045	1
 318	0	-5.92458725	0.00266578537	0.0038510506602204577	0
 319	0	1.35382557	0.7947544	2.2845767018893883	1
 320	1	5.988476	0.9974988	0.0036129742419820916	1
-321	0				
+321	0				0
 322	0	-5.07121468	0.006235666	0.0090243302579491296	0
 323	1	4.28225327	0.986376643	0.019789456912749203	1
 324	0	-6.14459133	0.002140461	0.0030913421022840675	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.58592224	0.0100914678	0.014632868867702545	0
 409	0	-5.205141	0.00545831956	0.0078962603748794508	0
 410	0	-6.57601929	0.0013914461	0.0020088303041534395	0
-411	0				
+411	0				0
 412	1	7.70175171	0.9995482	0.00065196153701951257	1
 413	0	-3.70033741	0.02411908	0.035222977147123087	0
 414	1	5.41945839	0.99559	0.006376396588275309	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.112665	0.00220974674	0.003191518193469859	0
 615	0	-4.37095165	0.012481451	0.018120247723782505	0
 616	0	-5.50264263	0.00405943953	0.0058684526611357517	0
-617	0				
+617	0				0
 618	0	-4.965955	0.006923029	0.010022553277705419	0
 619	0	-4.429267	0.0117827384	0.017099838701332234	0
 620	0	-5.50264263	0.00405943953	0.0058684526611357517	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt
index 4a5221f10c..43409b9917 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	4.28022528	0.9863494	0.019829298264044417	1
 35	0	-4.29419041	0.0134638669	0.019556202484947195	0
 37	0	-1.95759869	0.123727158	0.19054794774570458	0
-40	0				
+40	0				0
 41	1	1.34579754	0.7934417	0.33380384997661361	1
 44	1	5.22175264	0.9946311	0.0077665361772382407	1
 45	0	-4.55969143	0.0103568994	0.015019761369081966	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-3.50701833	0.0291131958	0.042624993467054707	0
 141	0	-4.510108	0.0108776484	0.015779105577069866	0
 144	0	-4.29419041	0.0134638669	0.019556202484947195	0
-145	0				
+145	0				0
 147	0	-4.118532	0.0160079524	0.023281438797448952	0
 150	0	-4.43784046	0.0116833262	0.016954714516170224	0
 151	1	2.86513376	0.9460957	0.079941963974142813	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-4.792855	0.008220622	0.011908867541972762	0
 156	0	-4.152423	0.0154827805	0.022511655407603286	0
 161	0	-3.361469	0.0335215963	0.049190599682179155	0
-164	0				
+164	0				0
 167	1	3.00652266	0.9528679	0.069651835538374979	1
 169	0	-4.76463461	0.008453925	0.012248282163630898	0
 171	0	-4.36102	0.0126044592	0.01829996516606797	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	7.761687	0.9995744	0.00061410874818056485	1
 247	1	2.24705172	0.904395938	0.14497358262585658	1
 248	0	-2.75623083	0.05973572	0.088861781570551343	0
-249	0				
+249	0				0
 250	0	-4.36834049	0.0125136767	0.018167327858314108	0
 252	0	2.47272253	0.9222073	3.6842213333365441	1
 254	1	5.30986643	0.9950817	0.0071130806432035459	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-4.36102	0.0126044592	0.01829996516606797	0
 271	0	-3.23003125	0.0380511023	0.055967840193562365	0
 272	1	1.97665262	0.878323853	0.18717511071531998	1
-275	0				
+275	0				0
 276	0	-4.011443	0.0177852046	0.025889540399059593	0
 277	0	-4.57693768	0.010181617	0.014764258553784819	0
 278	0	-4.36102	0.0126044592	0.01829996516606797	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-4.36102	0.0126044592	0.01829996516606797	0
 293	1	3.50341845	0.9707849	0.042776422691022505	1
 296	0	0.854511261	0.701512635	1.7442582303419563	1
-297	0				
+297	0				0
 299	1	4.02451658	0.9824417	0.025556263019683039	1
 300	1	4.165831	0.9847203	0.02221411037855156	1
 301	0	-4.36102	0.0126044592	0.01829996516606797	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	2.756329	0.940269768	0.088853362072482428	1
 317	1	5.80636454	0.9970007	0.004333585623359653	1
 319	0	1.0757966	0.7456977	1.975383454841898	1
-321	0				
+321	0				0
 323	1	3.082415	0.956161559	0.064673689924879513	1
 327	0	-4.57693768	0.010181617	0.014764258553784819	0
 328	1	2.805962	0.942997158	0.084674672619554123	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	9.154173	0.999894261	0.00015255667702522208	1
 613	0	-3.88851619	0.0200648643	0.029241838018723456	0
 614	0	-4.371011	0.0124807227	0.018119183737570529	0
-617	0				
+617	0				0
 618	0	-3.72869563	0.0234605316	0.034249740786795546	0
 619	0	-3.44594836	0.0308899172	0.045267541796380997	0
 621	0	-0.782016754	0.3138854	0.54347850919806506	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-3.6590457	0.0251103118	0.036689112229595131	0
 19	0	-2.927483	0.0508115776	0.075233591312011905	0
 22	0	-4.14026976	0.0156691261	0.022784748886103094	0
-23	1				
+23	1				0
 24	0	-4.75638962	0.008523319	0.012349253326730132	0
 26	0	-3.93837214	0.0191076845	0.027833331950969452	0
 27	0	-3.40870714	0.03202445	0.046957488715061987	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-4.14026976	0.0156691261	0.022784748886103094	0
 135	0	-2.62711	0.06741392	0.1006911970043132	0
 136	0	-3.77448845	0.0224339925	0.032733975062274864	0
-139	0				
+139	0				0
 140	0	-4.255713	0.0139846308	0.020317960583175827	0
 142	1	1.9862442	0.879345238	0.18549840430247841	1
 143	0	-3.74331784	0.02312786	0.033758349764067219	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-3.267953	0.0366871059	0.053923618256310278	0
 155	1	1.88906479	0.8686489	0.20315494639328185	1
 157	0	-4.39060831	0.0122414771	0.017769705367455636	0
-158	0				
+158	0				0
 159	1	6.88715744	0.9989802	0.001471976257367614	1
 160	1	5.57244873	0.996213257	0.0054734847881935346	1
 162	0	-4.024827	0.0175529048	0.025548374564996635	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	4.531541	0.989350557	0.015446292097008558	1
 232	0	0.251759052	0.562609434	1.1930059918223119	1
 234	0	-2.51516485	0.0748018846	0.11216576762239737	0
-235	0				
+235	0				0
 236	1	5.772835	0.9968987	0.0044811669482472481	1
 238	1	6.65452766	0.9987135	0.0018572316949005939	1
 243	0	-3.28154564	0.036209736	0.053208867556931244	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	8.09413	0.999694765	0.00044042879818134223	1
 287	0	-4.14026976	0.0156691261	0.022784748886103094	0
 289	1	4.30420876	0.9866685	0.019362604522295365	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	3.601099	0.973431468	0.038848681676236112	1
 298	0	-2.22490883	0.09753586	0.14805849380018501	0
 302	1	8.018049	0.9996706	0.00047526633912005399	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-4.75638962	0.008523319	0.012349253326730132	0
 310	0	-4.506051	0.0109213842	0.015842898366274911	0
 313	0	-4.987275	0.00677798	0.0098118479335557937	0
-315	0				
+315	0				0
 318	0	-4.75638962	0.008523319	0.012349253326730132	0
 320	1	2.81792259	0.943636656	0.08369663336324043	1
 322	0	-4.024827	0.0175529048	0.025548374564996635	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-4.87183237	0.00760109862	0.011007956774122585	0
 408	0	-3.31706572	0.03499035	0.051384728090851442	0
 410	0	-4.87183237	0.00760109862	0.011007956774122585	0
-411	0				
+411	0				0
 412	1	5.23884	0.9947216	0.007635302704268032	1
 417	0	-4.87183237	0.00760109862	0.011007956774122585	0
 420	0	-2.70138979	0.0628913939	0.093711836328273818	0
diff --git a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt
index ff73fc5189..3b2e2b7470 100644
--- a/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	3.96267843	0.9813426	0.027171185979008489	1
 21	1	5.265054	0.9948575	0.0074382155674881083	1
 22	0	-4.51155567	0.0108620832	0.015756402974357524	0
-23	1				
+23	1				0
 24	0	-5.107146	0.00601691334	0.0087067913827365544	0
 25	1	0.6726794	0.6621029	0.59487269328676762	1
 26	0	-4.36255264	0.0125854	0.018272117354929882	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-2.04001045	0.115065664	0.17635768683092809	0
 38	1	3.6194644	0.973902345	0.038150977482211336	1
 39	1	0.673018932	0.6621788	0.59470724065030856	1
-40	0				
+40	0				0
 41	1	1.75375986	0.8524264	0.23035280375662126	1
 42	1	5.60796976	0.9963449	0.0052828205055256471	1
 43	1	-0.5184488	0.37321502	1.4219210475645763	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.10382557	0.0162412636	0.023623552162962799	0
 137	0	-4.73142624	0.008736885	0.01266004645418743	0
 138	0	-3.874074	0.0203508064	0.029662873497674963	0
-139	0				
+139	0				0
 140	0	-4.73142624	0.008736885	0.01266004645418743	0
 141	0	-5.13915634	0.00582846347	0.0084332958699167727	0
 142	1	2.53462648	0.9265339	0.11008436686792368	1
 143	0	-4.1287837	0.0158472732	0.02304587572398243	0
 144	0	-4.919286	0.00725137955	0.010499643937654568	0
-145	0				
+145	0				0
 146	1	0.185849667	0.546329141	0.87215771785369722	1
 147	0	-4.93812275	0.007117027	0.010304411526052911	0
 148	0	-2.08798218	0.110270388	0.16856112656874939	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.24833822	0.9045071	0.14479626651911345	1
 156	0	-4.913893	0.007290303	0.010556209568305783	0
 157	0	-4.69941568	0.009018519	0.013069997580773615	0
-158	0				
+158	0				0
 159	1	8.213823	0.9997292	0.0003907114930137318	1
 160	1	6.409885	0.9983575	0.0023716112041259128	1
 161	0	-3.70981741	0.0238969475	0.034894625912887001	0
 162	0	-4.29168558	0.0134971775	0.019604916230060426	0
 163	0	-4.20999336	0.0146292737	0.021261482597556794	0
-164	0				
+164	0				0
 165	0	-3.35529184	0.0337223038	0.049490233625727506	0
 166	1	5.13335562	0.9941378	0.0084822193431077515	1
 167	1	4.31503153	0.986810148	0.019155543364578753	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.387140751	0.5955942	1.3061245037640643	1
 233	1	4.22282743	0.9855546	0.020992330945643928	1
 234	0	-2.79013348	0.0578596778	0.085986144354393876	0
-235	0				
+235	0				0
 236	1	7.198673	0.999253	0.0010781320275837761	1
 237	1	4.24964952	0.9859315	0.020440656601130012	1
 238	1	7.93097258	0.9996407	0.00051844885378563097	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.043116	0.9996788	0.00046348169408102081	1
 247	1	2.170814	0.8975978	0.15585897141376154	1
 248	0	-3.01326466	0.0468302034	0.069194857755858583	0
-249	0				
+249	0				0
 250	0	-5.133764	0.005859794	0.0084787621145538308	0
 251	1	5.4693675	0.9958038	0.0060666126630314994	1
 252	0	2.521253	0.925618351	3.7489094481346643	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.26803923	0.7804069	0.35770157547115156	1
 273	1	-0.341918468	0.415343523	1.2676230380461255	0
 274	0	-4.11754751	0.01602347	0.023304190486054636	0
-275	0				
+275	0				0
 276	0	-4.51155567	0.0108620832	0.015756402974357524	0
 277	0	-5.327016	0.00483505568	0.0069924288920724343	0
 278	0	-5.107146	0.00601691334	0.0087067913827365544	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	5.13687468	0.9941583	0.0084524642023233402	1
 290	0	-5.54688644	0.00388443237	0.005614963867042919	0
 291	0	-5.107146	0.00601691334	0.0087067913827365544	0
-292	1				
+292	1				0
 293	1	3.96790457	0.981438041	0.027030903251222888	1
-294	0				
+294	0				0
 295	1	4.55162954	0.9895601	0.015140724489837425	1
 296	0	0.6700988	0.661525249	1.5628798789895393	1
-297	0				
+297	0				0
 298	0	-2.40630245	0.08269336	0.12452401321321592	0
 299	1	4.497334	0.988984048	0.015980843395464565	1
 300	1	4.62145948	0.990257442	0.014124456553393392	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	1.84912252	0.864024043	0.21085663625525078	1
 313	0	-5.54688644	0.00388443237	0.005614963867042919	0
 314	0	-5.36138344	0.004672473	0.0067567510712633252	0
-315	0				
+315	0				0
 316	1	2.20764112	0.900933564	0.15050737158003294	1
 317	1	5.890983	0.997243345	0.0039825045312741787	1
 318	0	-5.00404263	0.006666029	0.0096492437155483984	0
 319	0	0.6469283	0.656317949	1.540853588056835	1
 320	1	3.99139547	0.9818612	0.026409039376297374	1
-321	0				
+321	0				0
 322	0	-4.29168558	0.0134971775	0.019604916230060426	0
 323	1	3.157802	0.959215045	0.060073807756361522	1
 324	0	-5.107146	0.00601691334	0.0087067913827365544	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-3.57900143	0.0271460768	0.039704898382857935	0
 409	0	-4.281804	0.0136293843	0.019798272915656116	0
 410	0	-5.327016	0.00483505568	0.0069924288920724343	0
-411	0				
+411	0				0
 412	1	6.193191	0.997960865	0.0029448527311883681	1
 413	0	-3.24647379	0.0374538042	0.055072312735252281	0
 414	1	4.55400229	0.9895846	0.015105009633995839	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-4.95365334	0.00700811762	0.010146170993954725	0
 615	0	-3.64432216	0.0254732724	0.037226341208279841	0
 616	0	-4.51155567	0.0108620832	0.015756402974357524	0
-617	0				
+617	0				0
 618	0	-4.10382557	0.0162412636	0.023623552162962799	0
 619	0	-3.696096	0.0242191125	0.035370869193417386	0
 620	0	-4.51155567	0.0108620832	0.015756402974357524	0
diff --git a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-CV-breast-cancer.txt
index 7cfbe77b4a..5c9bde6605 100644
--- a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	0.8960438	0.7101358	0.49383312022081494	1
 35	0	-1.47149158	0.186716	0.298168872554196	0
 37	0	-1.077555	0.253969	0.42269254099397019	0
-40	0				
+40	0				0
 41	1	-0.110265851	0.472461432	1.0817315302478872	0
 44	1	1.38623238	0.799990058	0.32194602419012386	1
 45	0	-1.49285364	0.1834938	0.29246424185161274	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.329715	0.2092065	0.33862709419515019	0
 141	0	-1.51333463	0.18044512	0.28708753442168577	0
 144	0	-1.47149158	0.186716	0.298168872554196	0
-145	0				
+145	0				0
 147	0	-1.36272907	0.203797117	0.3287919993163349	0
 150	0	-1.490515	0.183844447	0.29308395009459498	0
 151	1	0.488354921	0.6197188	0.69031438298058734	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-1.54631257	0.175619483	0.27861768553552435	0
 156	0	-1.34795034	0.206205666	0.33316283039965772	0
 161	0	-1.29642129	0.214767918	0.34880897708810421	0
-164	0				
+164	0				0
 167	1	0.7817354	0.686054	0.54360597630084673	1
 169	0	-1.52040219	0.1794023	0.28525299602441972	0
 171	0	-1.46262646	0.188065946	0.3005655398637459	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.30008841	0.908884346	0.13783136852928218	1
 247	1	0.283135176	0.5703147	0.81016986229628651	1
 248	0	-1.02733588	0.263600916	0.44144026210768955	0
-249	0				
+249	0				0
 250	0	-1.3897934	0.199440747	0.32091990872905618	0
 252	0	0.575369835	0.6400013	1.4739363860396681	1
 254	1	1.36448383	0.796487451	0.32827646395944027	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.46262646	0.188065946	0.3005655398637459	0
 271	0	-1.330715	0.209041134	0.33832542505991492	0
 272	1	0.3417368	0.58461237	0.77444774011663531	1
-275	0				
+275	0				0
 276	0	-1.43851376	0.1917756	0.30717219734355156	0
 277	0	-1.50446939	0.181759879	0.28940381583950159	0
 278	0	-1.46262646	0.188065946	0.3005655398637459	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.46262646	0.188065946	0.3005655398637459	0
 293	1	0.690094	0.665987849	0.58643223892348229	1
 296	0	0.122398376	0.530561447	1.090991766168943	1
-297	0				
+297	0				0
 299	1	0.8090725	0.6919118	0.53133991521179469	1
 300	1	1.07804394	0.7461236	0.42251343016986392	1
 301	0	-1.46262646	0.188065946	0.3005655398637459	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.633879662	0.653368652	0.61403085786632716	1
 317	1	1.75457263	0.852528632	0.2301798078479787	1
 319	0	0.1361382	0.5339821	1.1015427183713855	1
-321	0				
+321	0				0
 323	1	0.8411846	0.6987147	0.51722465664834216	1
 327	0	-1.50446939	0.181759879	0.28940381583950159	0
 328	1	0.758497	0.681027353	0.55421535102487163	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	2.80018759	0.942685962	0.085150850944065576	1
 613	0	-1.31009483	0.212470978	0.34459500515903269	0
 614	0	-1.49938011	0.18251799	0.29074111357003468	0
-617	0				
+617	0				0
 618	0	-1.40553582	0.196939126	0.31641874253214702	0
 619	0	-1.37255788	0.2022069	0.32591343959007929	0
 621	0	-0.609831333	0.35209766	0.62615172722986678	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.29125416	0.2156406	0.35041324245427652	0
 19	0	-1.18682528	0.233827218	0.38425832019246531	0
 22	0	-1.38527489	0.200163171	0.32222238184143043	0
-23	1				
+23	1				0
 24	0	-1.44789767	0.19032532	0.30458573193898042	0
 26	0	-1.321662	0.210541919	0.341065431407162	0
 27	0	-1.28084588	0.217406273	0.35366454853946033	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.36420059	0.203558445	0.3283595980104454	0
 135	0	-0.9835708	0.272183836	0.45835400169661483	0
 136	0	-1.33306038	0.2086536	0.33761874206668624	0
-139	0				
+139	0				0
 140	0	-1.42708111	0.1935539	0.31034997353186378	0
 142	1	0.5200758	0.6271655	0.67308190344279184	1
 143	0	-1.07713079	0.254049361	0.42284792669686094	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.147677	0.240913659	0.39766410362601251	0
 155	1	0.775262833	0.6846582	0.54654409786019487	1
 157	0	-1.39568317	0.198502019	0.31922920878555094	0
-158	0				
+158	0				0
 159	1	2.4702127	0.922027051	0.11711901622998303	1
 160	1	1.8089292	0.8592324	0.21887965615084526	1
 162	0	-1.34346867	0.206940219	0.33449847387485032	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1.80702519	0.859001935	0.21926671447669044	1
 232	0	-0.09305465	0.476753116	0.93443627885443414	0
 234	0	-0.7166654	0.3281277	0.57374106872220532	0
-235	0				
+235	0				0
 236	1	2.0308764	0.884000957	0.1778801634200064	1
 238	1	2.5700233	0.9289072	0.10639359546534205	1
 243	0	-0.9099059	0.2870191	0.48806467358561068	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	3.03633	0.954188645	0.067653576940859037	1
 287	0	-1.36420059	0.203558445	0.3283595980104454	0
 289	1	1.839293	0.8628651	0.21279308434601185	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	1.50403929	0.81817615	0.28951661133253503	1
 298	0	-1.01809835	0.265398	0.44496526256029006	0
 302	1	2.95740485	0.9506123	0.07307101604489151	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.44789767	0.19032532	0.30458573193898042	0
 310	0	-1.4164151	0.1952242	0.31334116395889644	0
 313	0	-1.53151011	0.17777285	0.28239108395025142	0
-315	0				
+315	0				0
 318	0	-1.38467479	0.200259253	0.32239570012101715	0
 320	1	1.03225207	0.737352252	0.43957409861257096	1
 322	0	-1.34346867	0.206940219	0.33449847387485032	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-1.48970389	0.183966175	0.29329914054619283	0
 408	0	-0.969954848	0.2748895	0.46372722780050113	0
 410	0	-1.48970389	0.183966175	0.29329914054619283	0
-411	0				
+411	0				0
 412	1	1.784699	0.8562761	0.22385204529486596	1
 417	0	-1.48970389	0.183966175	0.29329914054619283	0
 420	0	-0.827743053	0.3041225	0.52309474947909951	0
diff --git a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-CV-breast-cancer.txt
index 0302f143a8..98a63fcdf3 100644
--- a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	5.83416653	0.997082651	0.0042149967260249437	1
 35	0	-5.20735168	0.005446332	0.0078788712300762211	0
 37	0	-2.71164179	0.0622898862	0.092786101770516077	0
-40	0				
+40	0				0
 41	1	1.76036549	0.853255451	0.22895036937850363	1
 44	1	7.40955639	0.999394953	0.00087316212305162816	1
 45	0	-5.421812	0.004399689	0.0063614137834035649	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.322978	0.0130867995	0.019004890409612719	0
 141	0	-5.4411335	0.00431586	0.0062399450406013428	0
 144	0	-5.20735168	0.005446332	0.0078788712300762211	0
-145	0				
+145	0				0
 147	0	-4.875398	0.00757424766	0.010968922848962245	0
 150	0	-5.39204836	0.00453200564	0.006553162786217457	0
 151	1	4.061223	0.9830638	0.024643020624724253	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-5.73325	0.00322609954	0.0046618015694471927	0
 156	0	-4.91463	0.007284973	0.010548463613035559	0
 161	0	-4.12887526	0.0158458445	0.023043781432081138	0
-164	0				
+164	0				0
 167	1	4.796111	0.9918059	0.011870271192039138	1
 169	0	-5.68914	0.00337109854	0.0048716832359580091	0
 171	0	-5.265687	0.005139294	0.0074335520922891698	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	10.8528	0.9999806	2.7947451458241805E-05	1
 247	1	3.03624249	0.95418483	0.06765934462197544	1
 248	0	-3.08702755	0.04364554	0.064382659498109923	0
-249	0				
+249	0				0
 250	0	-5.14841127	0.00577508053	0.0083558311280958943	0
 252	0	3.84936237	0.979150653	5.5838539825714451	1
 254	1	7.35057163	0.9993582	0.00092625186884288718	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.265687	0.005139294	0.0074335520922891698	0
 271	0	-4.097221	0.016347127	0.023778810630558714	0
 272	1	2.79984665	0.942667544	0.085179038039461821	1
-275	0				
+275	0				0
 276	0	-4.915235	0.007280598	0.010542105680653375	0
 277	0	-5.49946833	0.00407229364	0.0058870729354622087	0
 278	0	-5.265687	0.005139294	0.0074335520922891698	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.265687	0.005139294	0.0074335520922891698	0
 293	1	4.736758	0.991309166	0.012593024732102163	1
 296	0	1.75365162	0.85241276	2.760360102190484	1
-297	0				
+297	0				0
 299	1	5.53140068	0.9960552	0.0057024187918531082	1
 300	1	6.04150867	0.9976277	0.0034266068641119179	1
 301	0	-5.265687	0.005139294	0.0074335520922891698	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	4.025776	0.9824635	0.025524315591638584	1
 317	1	8.423935	0.9997805	0.00031674081892699212	1
 319	0	1.82892418	0.861633539	2.8534338101579171	1
-321	0				
+321	0				0
 323	1	4.504982	0.9890671	0.015859728309184334	1
 327	0	-5.49946833	0.00407229364	0.0058870729354622087	0
 328	1	4.454892	0.9885119	0.016669732083571809	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	13.2412815	0.9999982	2.5797420694119618E-06	1
 613	0	-4.637956	0.009584702	0.013894495676017315	0
 614	0	-5.333713	0.00480293762	0.0069458679549985972	0
-617	0				
+617	0				0
 618	0	-4.623119	0.009726578	0.014101176192227349	0
 619	0	-4.331002	0.0129835671	0.018853990456118342	0
 621	0	-0.969069	0.2750661	0.46407865469425469	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.77261448	0.00838729553	0.012151339639068351	0
 19	0	-4.05630064	0.01701831	0.02476355221691592	0
 22	0	-5.26293468	0.00515338546	0.0074539868149001397	0
-23	1				
+23	1				0
 24	0	-5.847086	0.00287998538	0.0041609352152631573	0
 26	0	-5.01217842	0.00661237258	0.0095713166824383505	0
 27	0	-4.54662037	0.0104917344	0.015216336343473301	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.25242233	0.005207562	0.0075325538981779582	0
 135	0	-3.511651	0.028982535	0.042430850287558594	0
 136	0	-4.90477753	0.0073565715	0.010652520453755514	0
-139	0				
+139	0				0
 140	0	-5.39509726	0.00451827142	0.0065332584338255633	0
 142	1	2.2592926	0.9054491	0.14329456494743992	1
 143	0	-4.372905	0.0124574006	0.018085112102952432	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.16768646	0.01525183	0.022173264390610525	0
 155	1	2.62865639	0.9326832	0.10054091831709649	1
 157	0	-5.488929	0.004115263	0.0059493194428234175	0
-158	0				
+158	0				0
 159	1	8.939568	0.9998689	0.00018910731810054123	1
 160	1	6.86695	0.9989594	0.0015020181784367139	1
 162	0	-5.13077164	0.00587725034	0.0085040948177142958	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.89666176	0.9972589	0.0039599989302112676	1
 232	0	-0.179828167	0.455163717	0.87610531376236689	0
 234	0	-3.15223122	0.04100345	0.060402470875188088	0
-235	0				
+235	0				0
 236	1	7.74873161	0.9995689	0.00062210936850165717	1
 238	1	9.156269	0.99989444	0.00015229867579129541	1
 243	0	-3.844254	0.0209539	0.030551300678084092	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.8717079	0.999981	2.7431493603031304E-05	1
 287	0	-5.25242233	0.005207562	0.0075325538981779582	0
 289	1	6.0516243	0.9976515	0.0033921289521523556	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.83148575	0.992088437	0.011459363337312383	1
 298	0	-3.31150723	0.0351785272	0.051666079123835182	0
 302	1	10.6722527	0.9999768	3.3451013395372324E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.847086	0.00287998538	0.0041609352152631573	0
 310	0	-5.61057949	0.00364560937	0.005269112963217676	0
 313	0	-6.111411	0.00221251347	0.0031955185815049345	0
-315	0				
+315	0				0
 318	0	-5.81555	0.002971982	0.0042940476081927553	0
 320	1	3.90395832	0.98023653	0.028798182473169599	1
 322	0	-5.13077164	0.00587725034	0.0085040948177142958	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-5.97924852	0.002524339	0.0036464555896367997	0
 408	0	-4.06157875	0.01693024	0.024634297974768089	0
 410	0	-5.97924852	0.002524339	0.0036464555896367997	0
-411	0				
+411	0				0
 412	1	6.142968	0.9978561	0.003096342326011223	1
 417	0	-5.97924852	0.002524339	0.0036464555896367997	0
 420	0	-3.33492	0.0343924649	0.050491160716171948	0
diff --git a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt
index 22409b2a5a..85bae57a85 100644
--- a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	4.078068	0.983342052	0.024234755458090462	1
 21	1	5.07943726	0.993815064	0.0089506841986991444	1
 22	0	-6.401946	0.00165558141	0.0023904784483303873	0
-23	1				
+23	1				0
 24	0	-6.95376	0.000954126066	0.0013771700453364219	0
 25	1	0.131910324	0.532929838	0.90798248584253316	1
 26	0	-6.20803738	0.00200913986	0.0029014918436988269	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-3.97515774	0.018430287	0.026837360561959296	0
 38	1	3.85910988	0.9793487	0.030105439588229164	1
 39	1	0.289131165	0.5717834	0.806459299491597	1
-40	0				
+40	0				0
 41	1	0.5163593	0.626296043	0.67508333009285992	1
 42	1	6.25112057	0.9980754	0.0027792492014372186	1
 43	1	-1.67306614	0.158015817	2.6618591152960773	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-6.01794958	0.00242874329	0.0035081978824050039	0
 137	0	-6.618124	0.00133415242	0.0019260601909807822	0
 138	0	-5.72209167	0.0032621813	0.0047140259759722502	0
-139	0				
+139	0				0
 140	0	-6.618124	0.00133415242	0.0019260601909807822	0
 141	0	-7.00212	0.00090912357	0.0013121846250039875	0
 142	1	1.86599445	0.8659941	0.20757090594664257	1
 143	0	-5.405919	0.00446985662	0.0064630953185838089	0
 144	0	-6.785942	0.00112826866	0.001628666561573529	0
-145	0				
+145	0				0
 146	1	-0.2344532	0.441653728	1.17901240396708	0
 147	0	-6.632551	0.00131506776	0.0018984903241446914	0
 148	0	-3.505578	0.0291539337	0.042685529480640867	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.2497673	0.9046305	0.14459948541676573	1
 156	0	-6.63783455	0.0013081471	0.0018884928122825894	0
 157	0	-6.569764	0.00140016491	0.0020214264686188826	0
-158	0				
+158	0				0
 159	1	9.262019	0.99990505	0.00013699068516156971	1
 160	1	6.81782627	0.9989071	0.001577599187795759	1
 161	0	-5.57644749	0.00377171184	0.005451717595353108	0
 162	0	-6.18576765	0.002054292	0.0029667652410511319	0
 163	0	-5.441502	0.00431427639	0.0062376503223464629	0
-164	0				
+164	0				0
 165	0	-5.081398	0.00617287867	0.0089331816190877534	0
 166	1	5.99673557	0.9975193	0.0035833193575627669	1
 167	1	4.04529858	0.982796669	0.025035126906624509	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.9520569	0.278471351	0.47087141475726779	0
 233	1	4.02608871	0.982468843	0.025516438252352936	1
 234	0	-4.248459	0.0140850125	0.020464842181276369	0
-235	0				
+235	0				0
 236	1	8.120999	0.9997029	0.00042873045458892818	1
 237	1	3.97880173	0.9816355	0.02674065507190734	1
 238	1	9.321572	0.999910533	0.00012907875367543245	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.005473	0.9998773	0.00017706700464490148	1
 247	1	1.74156952	0.8508863	0.23296175567699981	1
 248	0	-4.675151	0.009237982	0.013389533098992946	0
-249	0				
+249	0				0
 250	0	-6.85401249	0.00105410081	0.0015215480827833656	0
 251	1	5.57425	0.996220052	0.0054636445480688526	1
 252	0	2.525447	0.9259066	3.7545111242363967	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.04092026	0.73902756	0.43629992864352879	1
 273	1	-1.54782867	0.1754001	2.5112785805368674	0
 274	0	-5.9604435	0.002572135	0.0037155870547972859	0
-275	0				
+275	0				0
 276	0	-6.401946	0.00165558141	0.0023904784483303873	0
 277	0	-7.16993856	0.0007687785	0.0011095394740419171	0
 278	0	-6.95376	0.000954126066	0.0013771700453364219	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	5.963811	0.997436464	0.0037031495249571483	1
 290	0	-7.386117	0.0006194141	0.0008939025092919693	0
 291	0	-6.95376	0.000954126066	0.0013771700453364219	0
-292	1				
+292	1				0
 293	1	3.82977867	0.97874707	0.030992011604895862	1
-294	0				
+294	0				0
 295	1	4.92571831	0.992794752	0.010432605435470237	1
 296	0	-0.00817585	0.497956038	0.9941143927175089	0
-297	0				
+297	0				0
 298	0	-4.33488274	0.0129339322	0.018781442391253584	0
 299	1	4.3436203	0.987177134	0.018619117824464626	1
 300	1	4.40119934	0.987885952	0.017583597598896144	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.9174366	0.7145195	0.48495470886222203	1
 313	0	-7.386117	0.0006194141	0.0008939025092919693	0
 314	0	-7.21227646	0.0007369329	0.001063561390310713	0
-315	0				
+315	0				0
 316	1	2.16819382	0.897356749	0.15624644520733796	1
 317	1	6.37115574	0.998292744	0.0024651544582865699	1
 318	0	-6.826747	0.00108320534	0.0015635819620021878	0
 319	0	-0.115743637	0.471096337	0.91892312744499838	0
 320	1	4.11173058	0.9838846	0.023439022974424555	1
-321	0				
+321	0				0
 322	0	-6.18576765	0.002054292	0.0029667652410511319	0
 323	1	3.31629562	0.964983642	0.051423608112212277	1
 324	0	-6.95376	0.000954126066	0.0013771700453364219	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-5.098096	0.00607128069	0.0087857038468610767	0
 409	0	-6.106088	0.00222429563	0.0032125544404639546	0
 410	0	-7.16993856	0.0007687785	0.0011095394740419171	0
-411	0				
+411	0				0
 412	1	6.053849	0.9976567	0.0033846301153950954	1
 413	0	-5.12191772	0.00592920836	0.0085794995279385791	0
 414	1	4.639694	0.9904318	0.013870479681066349	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.82828045	0.00108154735	0.0015611874005433336	0
 615	0	-5.42623472	0.00438035838	0.0063334027525860032	0
 616	0	-6.401946	0.00165558141	0.0023904784483303873	0
-617	0				
+617	0				0
 618	0	-6.01794958	0.00242874329	0.0035081978824050039	0
 619	0	-5.633953	0.00356168649	0.0051475999586587254	0
 620	0	-6.401946	0.00165558141	0.0023904784483303873	0
diff --git a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt
index 5197b73592..953068fccb 100644
--- a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	2.322781	0.998222351	0.0025668874786068312	1
 35	0	-1.91525483	0.005915621	0.0085597800780180429	0
 37	0	-0.682821751	0.142692313	0.22211501491184898	0
-40	0				
+40	0				0
 41	1	0.809957266	0.9039319	0.14571398208584879	1
 44	1	2.73944569	0.999422848	0.00083289438051421241	1
 45	0	-1.94671428	0.0054360223	0.0078639160441893435	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.53363073	0.0164193157	0.023884691545080352	0
 141	0	-2.06519866	0.00395226665	0.0057132130161921821	0
 144	0	-1.91525483	0.005915621	0.0085597800780180429	0
-145	0				
+145	0				0
 147	0	-1.84313476	0.007179688	0.010395463465996112	0
 150	0	-1.97708547	0.005009752	0.0072457094989476683	0
 151	1	1.45099306	0.9815549	0.026859095208834581	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-2.1974268	0.00276787742	0.0039987395951823247	0
 156	0	-1.89696681	0.006213517	0.0089921755974289187	0
 161	0	-1.42502642	0.0218984671	0.031943861389482818	0
-164	0				
+164	0				0
 167	1	2.354064	0.998366237	0.0023589497379793915	1
 169	0	-2.21602869	0.00263251015	0.0038029171463890205	0
 171	0	-1.897539	0.006203974	0.008978322239894131	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	3.30174255	0.9998737	0.00018222712667875736	1
 247	1	0.629675865	0.8525092	0.23021269060466767	1
 248	0	-1.12171221	0.0483664	0.07152188601007381	0
-249	0				
+249	0				0
 250	0	-2.04691076	0.00415170472	0.0060021119500057712	0
 252	0	1.01602411	0.942604	4.12290612676055	1
 254	1	2.17657	0.997363031	0.0038093670302838936	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.897539	0.006203974	0.008978322239894131	0
 271	0	-1.368627	0.0254129283	0.037137010195002478	0
 272	1	0.765766859	0.8930476	0.16319106749073262	1
-275	0				
+275	0				0
 276	0	-1.78302681	0.008435549	0.012221545522817861	0
 277	0	-2.047483	0.00414531538	0.0059928556832883097	0
 278	0	-1.897539	0.006203974	0.008978322239894131	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.897539	0.006203974	0.008978322239894131	0
 293	1	1.17371225	0.961760044	0.056251103565820429	1
 296	0	0.4346769	0.773356	2.1415002561411738	1
-297	0				
+297	0				0
 299	1	2.019999	0.9959794	0.0058121507954068162	1
 300	1	2.2421217	0.9977903	0.0031914838554231535	1
 301	0	-1.897539	0.006203974	0.008978322239894131	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.9578371	0.9334789	0.099310694790810672	1
 317	1	2.6748023	0.999312758	0.00099182083151890563	1
 319	0	0.702352047	0.87553966	3.0062420076587428	1
-321	0				
+321	0				0
 323	1	1.138917	0.9581469	0.061681187824867326	1
 327	0	-2.047483	0.00414531538	0.0059928556832883097	0
 328	1	0.998517036	0.9399896	0.089283259387362562	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	5.011583	0.999998748	1.8058189642293044E-06	1
 613	0	-1.848559	0.00707593327	0.010244702155254935	0
 614	0	-1.9948014	0.0047766366	0.006907740990800825	0
-617	0				
+617	0				0
 618	0	-1.6507988	0.0120159388	0.017440327322179375	0
 619	0	-1.51857078	0.017089799	0.024868477463820319	0
 621	0	-0.159297943	0.406589121	0.75289671799437707	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-2.01459932	0.02046752	0.029834763390847389	0
 19	0	-1.722561	0.0706015	0.10563077935630806	0
 22	0	-2.18885	0.009580599	0.013888519789490289	0
-23	1				
+23	1				0
 24	0	-2.45265675	0.00300532184	0.0043422911736604322	0
 26	0	-2.15108967	0.0113010341	0.016396771634848997	0
 27	0	-1.8968116	0.0339725837	0.049863960916695586	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-2.18885	0.009580599	0.013888519789490289	0
 135	0	-1.67432666	0.0859358	0.12963259925365803	0
 136	0	-2.04283071	0.0181100331	0.026366733420336564	0
-139	0				
+139	0				0
 140	0	-2.21708131	0.00846625	0.012266215273071623	0
 142	1	-0.39607358	0.963921666	0.053012185419208942	0
 143	0	-2.12454414	0.0126899984	0.018424952871546458	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.87877429	0.03668837	0.053925509586129468	0
 155	1	-0.6914537	0.878659666	0.18662362559522522	0
 157	0	-2.30663776	0.005714676	0.0082681821048535484	0
-158	0				
+158	0				0
 159	1	0.826603651	0.9998317	0.00024285994311160547	1
 160	1	0.465637445	0.999170542	0.0011971518470987805	1
 162	0	-2.16061854	0.0108400183	0.015724220850716938	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	-0.0580048561	0.9916699	0.012068138193505744	0
 232	0	-1.12658465	0.5141482	1.0414117089703063	0
 234	0	-1.83982372	0.04328234	0.063834867527523209	0
-235	0				
+235	0				0
 236	1	0.979896069	0.999914467	0.00012340282955575714	1
 238	1	0.930060863	0.9998934	0.00015376068339360816	1
 243	0	-2.01161838	0.02073334	0.030226326896041298	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	1.41079044	0.999987245	1.8402261006614678E-05	1
 287	0	-2.18885	0.009580599	0.013888519789490289	0
 289	1	0.0753440857	0.9953623	0.0067063762389963991	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	-0.367047548	0.9681271	0.046731673516829733	0
 298	0	-1.44922507	0.202717274	0.32683668378040626	0
 302	1	1.39901066	0.9999866	1.9348177961999343E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-2.45265675	0.00300532184	0.0043422911736604322	0
 310	0	-2.33486915	0.00504769245	0.0073007223089671565	0
 313	0	-2.50911975	0.002343144	0.0033844089083832525	0
-315	0				
+315	0				0
 318	0	-2.45265675	0.00300532184	0.0043422911736604322	0
 320	1	0.09479761	0.995742738	0.006155041546569217	1
 322	0	-2.16061854	0.0108400183	0.015724220850716938	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.48088837	0.00265371148	0.0038335852528692412	0
 408	0	-2.10281515	0.0139513118	0.020269210492385212	0
 410	0	-2.48088837	0.00265371148	0.0038335852528692412	0
-411	0				
+411	0				0
 412	1	-0.0120434761	0.9931908	0.0098571608082237746	0
 417	0	-2.48088837	0.00265371148	0.0038335852528692412	0
 420	0	-1.86625433	0.0386949927	0.056933846240527428	0
diff --git a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt
index 1c905b24c8..105f99fc80 100644
--- a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.51313376	0.997060657	0.0042468207167790329	1
 21	1	1.88215756	0.9991858	0.0011751199613487565	1
 22	0	-1.5913856	0.006754517	0.0097777676588594702	0
-23	1				
+23	1				0
 24	0	-1.85515833	0.00270523666	0.0039081201011675363	0
 25	1	0.183981657	0.767693	0.38139863321618261	1
 26	0	-1.596403	0.006638234	0.0096088756803218642	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.48321867	0.244259775	0.40403768061841711	0
 38	1	1.01125383	0.983338952	0.024239302762828055	1
 39	1	-0.0106446743	0.62648654	0.67464458153125895	0
-40	0				
+40	0				0
 41	1	0.8607874	0.9721748	0.040712322202366577	1
 42	1	1.4849956	0.9967589	0.004683544378464086	1
 43	1	-0.7279444	0.121085733	3.0458992041721875	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.404305	0.0128827207	0.018706593545987932	0
 137	0	-1.701774	0.00460771844	0.0066628947272309403	0
 138	0	-1.360993	0.0149499336	0.021731041715098105	0
-139	0				
+139	0				0
 140	0	-1.701774	0.00460771844	0.0066628947272309403	0
 141	0	-1.8888545	0.00240627048	0.0034756978965475691	0
 142	1	0.881847143	0.974092543	0.037869253621396266	1
 143	0	-1.545697	0.007910921	0.01145843020471164	0
 144	0	-1.77846622	0.00353102176	0.0051032026604077695	0
-145	0				
+145	0				0
 146	1	-0.216273546	0.450334132	1.1509322683430081	0
 147	0	-1.82796979	0.00297325244	0.0042958860993499966	0
 148	0	-0.7305672	0.12011648	0.18461554363807445	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.429970026	0.886195242	0.17430351324204957	1
 156	0	-1.92223477	0.0021426254	0.0030944713637373776	0
 157	0	-1.66807771	0.005178785	0.0074908208279084272	0
-158	0				
+158	0				0
 159	1	2.79265332	0.999965847	4.9273870913609948E-05	1
 160	1	2.08471417	0.999597847	0.00058030016510027748	1
 161	0	-1.23200977	0.0232356917	0.033917610773834123	0
 162	0	-1.48099709	0.009891603	0.014341615100451873	0
 163	0	-1.20272636	0.02566766	0.037514142314967996	0
-164	0				
+164	0				0
 165	0	-1.09945023	0.0363804549	0.053464438820388052	0
 166	1	1.35837817	0.99497056	0.0072742561293771086	1
 167	1	1.40636182	0.9957416	0.0061566823680882154	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.0236132145	0.6158536	1.3802718900263455	0
 233	1	1.45269513	0.9963742	0.005240444497289571	1
 234	0	-1.12313449	0.0335955	0.049300920379201259	0
-235	0				
+235	0				0
 236	1	2.801736	0.9999669	4.7725975020197848E-05	1
 237	1	1.18725443	0.9909072	0.013178153095375312	1
 238	1	2.58363461	0.999929249	0.00010207531428030829	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.15890861	0.9996894	0.00044817040124598361	1
 247	1	0.7686317	0.9620387	0.055833170607592193	1
 248	0	-0.9843831	0.0533667132	0.079122441964183776	0
-249	0				
+249	0				0
 250	0	-2.03262329	0.001459477	0.0021071182550953969	0
 251	1	1.98737311	0.999435544	0.0008145677672951316	1
 252	0	0.938287735	0.9786189	5.5475214513768956	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.364958525	0.861275733	0.21545291272160746	1
 273	1	-0.0762293339	0.5716655	0.80675680440858633	0
 274	0	-1.41909039	0.0122437514	0.017773027141160865	0
-275	0				
+275	0				0
 276	0	-1.5913856	0.006754517	0.0097777676588594702	0
 277	0	-1.96554685	0.00184303813	0.0026613952529717312	0
 278	0	-1.85515833	0.00270523666	0.0039081201011675363	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.51208711	0.99705	0.0042622586236973218	1
 290	0	-2.07593513	0.00125529012	0.0018121384446850468	0
 291	0	-1.85515833	0.00270523666	0.0039081201011675363	0
-292	1				
+292	1				0
 293	1	1.33046842	0.9944597	0.0080152036111407286	1
-294	0				
+294	0				0
 295	1	1.2251215	0.9920222	0.011555664783429847	1
 296	0	0.111403227	0.719591737	1.8343992308763424	1
-297	0				
+297	0				0
 298	0	-0.7513188	0.112681925	0.17247673834356275	0
 299	1	1.96303582	0.9993856	0.00088667099785278705	1
 300	1	1.383044	0.995382845	0.0066765713113142704	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.17001605	0.7589018	0.39801492605707506	1
 313	0	-2.07593513	0.00125529012	0.0018121384446850468	0
 314	0	-1.97056413	0.00181115558	0.0026153142649758387	0
-315	0				
+315	0				0
 316	1	0.541802645	0.9199835	0.12032009864475471	1
 317	1	1.56700492	0.9975625	0.0035208219605770688	1
 318	0	-1.84010613	0.00285049225	0.0041182633675105971	0
 319	0	0.05099702	0.675234735	1.6225307564202673	1
 320	1	1.7057507	0.9984955	0.0021721414278146082	1
-321	0				
+321	0				0
 322	0	-1.48099709	0.009891603	0.014341615100451873	0
 323	1	0.7110567	0.95399344	0.067948749601842412	1
 324	0	-1.85515833	0.00270523666	0.0039081201011675363	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-1.45910537	0.0106672905	0.015472318523715401	0
 409	0	-1.54807365	0.007846191	0.011364302031181555	0
 410	0	-1.96554685	0.00184303813	0.0026613952529717312	0
-411	0				
+411	0				0
 412	1	1.61123109	0.9979099	0.0030185274243607983	1
 413	0	-1.063524	0.0410328656	0.060446722723610943	0
 414	1	1.54281878	0.9973487	0.0038300596622238277	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.78348351	0.00347004039	0.0050149160869795298	0
 615	0	-1.31768119	0.0173430257	0.025240206070453266	0
 616	0	-1.5913856	0.006754517	0.0097777676588594702	0
-617	0				
+617	0				0
 618	0	-1.404305	0.0128827207	0.018706593545987932	0
 619	0	-1.21722436	0.024434112	0.035688781701501276	0
 620	0	-1.5913856	0.006754517	0.0097777676588594702	0
diff --git a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-TrainTest-breast-cancer.txt
index ff963fe7a2..d31e2e0f16 100644
--- a/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SDCA/BinarySDCA-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.37743354	0.7985785	0.32449386248842338	1
 21	1	1.7630446	0.853590548	0.22838389385799779	1
 22	0	-1.874893	0.132976577	0.20585712538187464	0
-23	1				
+23	1				0
 24	0	-1.948468	0.124720506	0.19218432401279964	0
 25	1	0.243255854	0.5605158	0.83517300013076445	1
 26	0	-1.79869926	0.142009482	0.22096639052344227	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.30918431	0.212623373	0.34487420705553562	0
 38	1	1.52097869	0.8206825	0.28510385981645775	1
 39	1	0.568297148	0.638370156	0.64753488753370236	1
-40	0				
+40	0				0
 41	1	0.08091617	0.520218	0.94281173541226504	1
 42	1	2.4137857	0.9178725	0.12363434755323521	1
 43	1	-0.08661461	0.478359878	1.0638317048217665	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.80893993	0.1407663	0.21887750444885776	0
 137	0	-1.9332242	0.126394138	0.1949455575113978	0
 138	0	-1.70428443	0.153906524	0.24111103479242962	0
-139	0				
+139	0				0
 140	0	-1.9332242	0.126394138	0.1949455575113978	0
 141	0	-1.99917722	0.119289339	0.18325996439997919	0
 142	1	0.6176696	0.649688363	0.62218023037407078	1
 143	0	-1.44733071	0.190412715	0.3047414631100317	0
 144	0	-1.94084609	0.125554934	0.19356034047915699	0
-145	0				
+145	0				0
 146	1	0.272925377	0.567810953	0.81651741701068026	1
 147	0	-1.8198235	0.13945505	0.21667754281184065	0
 148	0	-0.713562	0.328812242	0.57521169167023078	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.9670353	0.7245282	0.46488626460347809	1
 156	0	-1.793424	0.142653435	0.22204959316054371	0
 157	0	-1.882515	0.132100269	0.20439971838260004	0
-158	0				
+158	0				0
 159	1	3.20693851	0.961094558	0.057249715926430703	1
 160	1	2.3220613	0.910687745	0.13497162539860094	1
 161	0	-1.65904641	0.159890041	0.25134992500211428	0
 162	0	-1.81656182	0.139846936	0.21733468482291701	0
 163	0	-1.60762358	0.166918814	0.26347099825296155	0
-164	0				
+164	0				0
 165	0	-1.50459647	0.181740969	0.28937047546414252	0
 166	1	2.457339	0.9210965	0.11857577878171396	1
 167	1	1.31327176	0.7880601	0.34362238392184646	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.213132143	0.446917742	0.85443403273590568	0
 233	1	1.23634028	0.774926364	0.36786886673349695	1
 234	0	-1.00412917	0.268130362	0.4503413991221501	0
-235	0				
+235	0				0
 236	1	2.65734458	0.934462249	0.097791712220334726	1
 237	1	1.59322524	0.8310694	0.26695912082718543	1
 238	1	3.30821967	0.9647097	0.051833223594515407	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	3.32132936	0.965153337	0.051169929428424521	1
 247	1	0.572052956	0.639236748	0.64557774708968529	1
 248	0	-1.29279661	0.215379834	0.34993367973529765	0
-249	0				
+249	0				0
 250	0	-1.85175514	0.135666952	0.21034077001927648	0
 251	1	1.686516	0.843765438	0.24508610192596253	1
 252	0	0.9327009	0.717622936	1.8243051828654713	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.5505221	0.6342567	0.65686119381445462	1
 273	1	-0.451063156	0.389108032	1.3617573340834921	0
 274	0	-1.72499943	0.151228324	0.23655158068052121	0
-275	0				
+275	0				0
 276	0	-1.874893	0.132976577	0.20585712538187464	0
 277	0	-2.00679922	0.1184909	0.18195262731195211	0
 278	0	-1.948468	0.124720506	0.19218432401279964	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	2.363632	0.914011657	0.12971552945936157	1
 290	0	-2.06513023	0.112532459	0.17223374110934919	0
 291	0	-1.948468	0.124720506	0.19218432401279964	0
-292	1				
+292	1				0
 293	1	1.17569327	0.764172554	0.38802965202562639	1
-294	0				
+294	0				0
 295	1	1.9321816	0.8734907	0.1951357665052601	1
 296	0	0.2875533	0.571397066	1.222286369266439	1
-297	0				
+297	0				0
 298	0	-1.39716244	0.198266774	0.31880583096618414	0
 299	1	1.31489539	0.788331151	0.34312631094095036	1
 300	1	1.6675427	0.8412479	0.24939706872810494	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.6733315	0.662248731	0.59455492152164024	1
 313	0	-2.06513023	0.112532459	0.17223374110934919	0
 314	0	-2.03932476	0.115135506	0.17647155325903272	0
-315	0				
+315	0				0
 316	1	0.9730499	0.725726962	0.46250122508222125	1
 317	1	2.53153682	0.9263233	0.11041230078378952	1
 318	0	-1.85089087	0.135768339	0.21051001013383977	0
 319	0	0.279238	0.5693594	1.2154438271457824	1
 320	1	1.35926127	0.795639634	0.32981295026166818	1
-321	0				
+321	0				0
 322	0	-1.81656182	0.139846936	0.21733468482291701	0
 323	1	1.28926969	0.7840235	0.35103115421599534	1
 324	0	-1.948468	0.124720506	0.19218432401279964	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-1.33084726	0.209019259	0.33828552617088203	0
 409	0	-1.77023745	0.1455128	0.22686922143757757	0
 410	0	-2.00679922	0.1184909	0.18195262731195211	0
-411	0				
+411	0				0
 412	1	2.25751042	0.9052964	0.14353790094246915	1
 413	0	-1.58000016	0.170795456	0.27020007178125394	0
 414	1	1.60186315	0.8322786	0.2648615365498318	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.97337174	0.122027189	0.18775183095640005	0
 615	0	-1.59962881	0.1680335	0.26540264924934215	0
 616	0	-1.874893	0.132976577	0.20585712538187464	0
-617	0				
+617	0				0
 618	0	-1.80893993	0.1407663	0.21887750444885776	0
 619	0	-1.74298692	0.148933932	0.23265696296547442	0
 620	0	-1.874893	0.132976577	0.20585712538187464	0
diff --git a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-CV-breast-cancer.txt
index 8b3d215017..f4e8911532 100644
--- a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	0.344691515	0.5853297	0.77267858291118818	1
 35	0	-0.6512495	0.342708021	0.60539371596619707	0
 37	0	-0.503962	0.376610041	0.68179317658398975	0
-40	0				
+40	0				0
 41	1	-0.09442055	0.4764124	1.069717174215209	0
 44	1	0.5798913	0.6410424	0.64150828626867074	1
 45	0	-0.6560674	0.341623574	0.60301541680763648	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-0.597589	0.354895473	0.63239515287919279	0
 141	0	-0.6678773	0.3389723	0.5972173671855312	0
 144	0	-0.6512495	0.342708021	0.60539371596619707	0
-145	0				
+145	0				0
 147	0	-0.6018609	0.353918076	0.63021098184538349	0
 150	0	-0.656989932	0.3414161	0.60256083089734203	0
 151	1	0.160812974	0.540116847	0.88865654739065503	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-0.67789495	0.336731285	0.59233461600767046	0
 156	0	-0.5912131	0.356356561	0.63566639957530646	0
 161	0	-0.5840918	0.3579916	0.63933593475596628	0
-164	0				
+164	0				0
 167	1	0.315922141	0.5783301	0.79003490476906479	1
 169	0	-0.6661818	0.33935234	0.59804704249396301	0
 171	0	-0.644639254	0.344198585	0.60866907932442826	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	0.9649427	0.7241103	0.46571861194179465	1
 247	1	0.07307994	0.51826185	0.94824689644610127	1
 248	0	-0.4621131	0.386484653	0.70482866116462817	0
-249	0				
+249	0				0
 250	0	-0.607840955	0.352551848	0.62716342858897578	0
 252	0	0.210040927	0.552318037	1.1594538998856256	1
 254	1	0.5551709	0.635334432	0.65441188637353787	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-0.644639254	0.344198585	0.60866907932442826	0
 271	0	-0.6045689	0.3532991	0.62882950155653372	0
 272	1	0.109180689	0.5272681	0.92339134731632821	1
-275	0				
+275	0				0
 276	0	-0.6412319	0.3449681	0.61036295013192154	0
 277	0	-0.6612671	0.340455025	0.60045705425766605	0
 278	0	-0.644639254	0.344198585	0.60866907932442826	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-0.644639254	0.344198585	0.60866907932442826	0
 293	1	0.2438618	0.560665131	0.83478874766701627	1
 296	0	0.0298114419	0.5074523	1.0216646747888918	1
-297	0				
+297	0				0
 299	1	0.29232645	0.5725656	0.80448706147450022	1
 300	1	0.440484524	0.6083745	0.71696846696669991	1
 301	0	-0.644639254	0.344198585	0.60866907932442826	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.23788023	0.5591912	0.83858636815416177	1
 317	1	0.736536	0.676237941	0.56439713300164063	1
 319	0	0.032892406	0.508222342	1.0239219003304794	1
-321	0				
+321	0				0
 323	1	0.3295461	0.581648946	0.78177941761076775	1
 327	0	-0.6612671	0.340455025	0.60045705425766605	0
 328	1	0.309677362	0.5768065	0.79384070845234189	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	1.18309152	0.7655032	0.38551963408922602	1
 613	0	-0.578392267	0.3593026	0.64228498181768678	0
 614	0	-0.663600147	0.339931339	0.59931199209014285	0
-617	0				
+617	0				0
 618	0	-0.6312144	0.347235233	0.61536490408676614	0
 619	0	-0.621196747	0.349509329	0.62039972730149728	0
 621	0	-0.2970261	0.426284641	0.80159295389429652	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-0.5587295	0.363841474	0.65254177576954708	0
 19	0	-0.521061659	0.372604	0.67255179238253271	0
 22	0	-0.597002566	0.355029762	0.63269550517202178	0
-23	1				
+23	1				0
 24	0	-0.6152313	0.3508668	0.62341353797116505	0
 26	0	-0.568058968	0.361684829	0.64765915777643768	0
 27	0	-0.559334755	0.3637014	0.6522241546694586	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-0.586384356	0.35746488	0.6381527823333405	0
 135	0	-0.4233432	0.395717025	0.72670379813371644	0
 136	0	-0.578168631	0.3593541	0.6424009484072789	0
-139	0				
+139	0				0
 140	0	-0.6164417	0.350591153	0.62280105585760936	0
 142	1	0.253997982	0.5631603	0.82838245949919198	1
 143	0	-0.455442041	0.388067663	0.70855595514156899	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-0.498274028	0.377946377	0.68488914380895782	0
 155	1	0.381782949	0.5943031	0.75072925773026189	1
 157	0	-0.5963973	0.355168372	0.63300558819075581	0
-158	0				
+158	0				0
 159	1	1.14907432	0.7593418	0.3971787124185161	1
 160	1	0.835970342	0.697615862	0.51949525142708575	1
 162	0	-0.5775634	0.359493434	0.64271473576785443	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	0.867232	0.7041694	0.50600557448041072	1
 232	0	-0.0153304338	0.496167481	0.98898385339386186	0
 234	0	-0.28234	0.4298802	0.81066299300396294	0
-235	0				
+235	0				0
 236	1	0.9360302	0.718297064	0.47734747567952907	1
 238	1	1.21385264	0.770979941	0.37523476983545384	1
 243	0	-0.3776855	0.406685263	0.7531304771823496	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	1.42419529	0.8059953	0.31115669483110281	1
 287	0	-0.586384356	0.35746488	0.6381527823333405	0
 289	1	0.8870376	0.7082785	0.49761139182067243	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	0.7293541	0.674663544	0.56775988879752004	1
 298	0	-0.4508557	0.389157325	0.711127239010238	0
 302	1	1.38025045	0.7990312	0.3236762608744207	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-0.6152313	0.3508668	0.62341353797116505	0
 310	0	-0.6052183	0.353150755	0.62849857907527806	0
 313	0	-0.654109538	0.342064053	0.60398095649539585	0
-315	0				
+315	0				0
 318	0	-0.5833766	0.358156025	0.63970545866432549	0
 320	1	0.483023465	0.618461549	0.69324419149565364	1
 322	0	-0.5775634	0.359493434	0.64271473576785443	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-0.6346704	0.3464523	0.61363554879852178	0
 408	0	-0.398791075	0.401602834	0.74082475334425091	0
 410	0	-0.6346704	0.3464523	0.61363554879852178	0
-411	0				
+411	0				0
 412	1	0.851157367	0.7008099	0.51290494780474771	1
 417	0	-0.6346704	0.3464523	0.61363554879852178	0
 420	0	-0.3393041	0.415978521	0.77590666598714197	0
diff --git a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-CV-breast-cancer.txt
index a2364522f6..a2bfaeeb70 100644
--- a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	0.6522908	0.9885379	0.01663180464505477	1
 35	0	-1.12420082	0.0107460516	0.015587176400536187	0
 37	0	-0.865502357	0.0386134759	0.056811513682664551	0
-40	0				
+40	0				0
 41	1	-0.1372056	0.6145622	0.70236902985400396	0
 44	1	1.0547893	0.9984863	0.0021854902279334833	1
 45	0	-1.13070083	0.0104023358	0.015085999817509936	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.03150129	0.0170594156	0.024823881934527593	0
 141	0	-1.15380061	0.00926659	0.0134311903289673	0
 144	0	-1.12420082	0.0107460516	0.015587176400536187	0
-145	0				
+145	0				0
 147	0	-1.03270125	0.0169580057	0.024675046951938132	0
 150	0	-1.13440084	0.0102115627	0.0148079061901775	0
 151	1	0.335192084	0.945543051	0.080784949020458824	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-1.17080045	0.008510069	0.012329973523626827	0
 156	0	-1.01700115	0.0183329377	0.026694285275120175	0
 161	0	-1.00710154	0.0192555338	0.028050804915513337	0
-164	0				
+164	0				0
 167	1	0.6017914	0.98525393	0.021432495728287648	1
 169	0	-1.15050054	0.009420992	0.013656046492446974	0
 171	0	-1.11160088	0.01144463	0.016606319988959024	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	1.7594862	0.999956965	6.208707291578748E-05	1
 247	1	0.172593474	0.8841638	0.17761443218515088	1
 248	0	-0.793102443	0.0547425	0.081220704071742325	0
-249	0				
+249	0				0
 250	0	-1.04660094	0.0158256628	0.0230141968119793	0
 252	0	0.423291922	0.964417338	4.8126817596940885	1
 254	1	1.03148985	0.998297453	0.0024583495418655562	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.11160088	0.01144463	0.016606319988959024	0
 271	0	-1.04360127	0.01606356	0.023362970756245272	0
 272	1	0.243792772	0.9162424	0.12619873583154692	1
-275	0				
+275	0				0
 276	0	-1.10720086	0.0116990069	0.016977604564195337	0
 277	0	-1.14120078	0.009869945	0.014310057532988397	0
 278	0	-1.11160088	0.01144463	0.016606319988959024	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.11160088	0.01144463	0.016606319988959024	0
 293	1	0.478191853	0.97280544	0.039776797794310127	1
 296	0	0.0886935	0.83318603	2.5836879844847194	1
-297	0				
+297	0				0
 299	1	0.5653906	0.9823277	0.025723714124946184	1
 300	1	0.8071904	0.994728446	0.0076253612609159995	1
 301	0	-1.11160088	0.01144463	0.016606319988959024	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.472591877	0.9720465	0.040902773075660377	1
 317	1	1.35288787	0.9996641	0.00048464251232972397	1
 319	0	0.100693226	0.841446757	2.6569607115771978	1
-321	0				
+321	0				0
 323	1	0.6351912	0.987516046	0.018123905012295945	1
 327	0	-1.14120078	0.009869945	0.014310057532988397	0
 328	1	0.5871916	0.9841424	0.023060980928491851	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	2.158784	0.9999943	8.2551908597278378E-06	1
 613	0	-0.993201256	0.0206282046	0.030071445887912274	0
 614	0	-1.14700067	0.009587526	0.013898610301947204	0
-617	0				
+617	0				0
 618	0	-1.090201	0.0127353743	0.018491259389232038	0
 619	0	-1.07320118	0.0138622615	0.020138926273650697	0
 621	0	-0.4947039	0.207426473	0.33538331559891793	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.02980137	0.0147205992	0.021395199721883466	0
 19	0	-0.9630018	0.0192868058	0.028096807322037363	0
 22	0	-1.0968008	0.011213962	0.016269722836470393	0
-23	1				
+23	1				0
 24	0	-1.13000059	0.00979631	0.014202769680513335	0
 26	0	-1.04700089	0.0137287723	0.019943648017493942	0
 27	0	-1.03000128	0.0147086745	0.021377739156459911	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.079601	0.0120263351	0.017455508586451673	0
 135	0	-0.7955023	0.03769685	0.055436642942084668	0
 136	0	-1.0634011	0.0128445318	0.018650780679196597	0
-139	0				
+139	0				0
 140	0	-1.13040054	0.009780362	0.014179534189705549	0
 142	1	0.3573923	0.8180728	0.2896988683892544	1
 143	0	-0.8376017	0.03189309	0.046761717990888088	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-0.917201638	0.0231931154	0.033854726268903304	0
 155	1	0.5948919	0.922758937	0.1159742899072022	1
 157	0	-1.09660089	0.0112230852	0.016283034217764617	0
-158	0				
+158	0				0
 159	1	1.88818586	0.9995909	0.00059036523296398255	1
 160	1	1.36718786	0.996521652	0.0050269435856363917	1
 162	0	-1.06320107	0.01285497	0.018666035936317264	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1.39838827	0.9969394	0.0044222533640880836	1
 232	0	-0.118705273	0.38808772	0.70860324232262772	0
 234	0	-0.57100296	0.08979461	0.13573597071280369	0
-235	0				
+235	0				0
 236	1	1.52918732	0.9982108	0.0025835996006501579	1
 238	1	1.96808636	0.9997055	0.00042494571667690465	1
 243	0	-0.703202665	0.0541654155	0.080340199841784268	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	2.32438421	0.999932	9.8119438852589428E-05	1
 287	0	-1.079601	0.0120263351	0.017455508586451673	0
 289	1	1.42798841	0.99728936	0.0039159372565436843	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	1.171589	0.9922556	0.011216254621805593	1
 298	0	-0.8448025	0.0309909787	0.045417997957015462	0
 302	1	2.26218414	0.999912143	0.00012675678201834402	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.13000059	0.00979631	0.014202769680513335	0
 310	0	-1.11300075	0.0104985284	0.015226241971828952	0
 313	0	-1.19720018	0.007447739	0.010785028389452023	0
-315	0				
+315	0				0
 318	0	-1.07840109	0.0120851332	0.017541371482030246	0
 320	1	0.77709043	0.961948335	0.055968683838555341	1
 322	0	-1.06320107	0.01285497	0.018666035936317264	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-1.16360033	0.008542378	0.012376987044267063	0
 408	0	-0.7606021	0.0432654768	0.063809436873055653	0
 410	0	-1.16360033	0.008542378	0.012376987044267063	0
-411	0				
+411	0				0
 412	1	1.35098827	0.9962829	0.0053726686646499901	1
 417	0	-1.16360033	0.008542378	0.012376987044267063	0
 420	0	-0.6557027	0.0650944263	0.097107435980156739	0
diff --git a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt
index 9dec61f554..deb3abc49a 100644
--- a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.222367	0.9828292	0.024987354577091989	1
 21	1	1.49796534	0.9935609	0.0093196803205346252	1
 22	0	-1.19740391	0.009379565	0.013595712679399167	0
-23	1				
+23	1				0
 24	0	-1.23810339	0.008112156	0.01175109505221196	0
 25	1	0.3802781	0.7344174	0.4453278964846259	1
 26	0	-1.14100432	0.01146578	0.016637187062001499	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.79460907	0.0387752019	0.057054226638771945	0
 38	1	1.34886718	0.989039242	0.015900330726329494	1
 39	1	0.6641748	0.8848001	0.17657658460400094	1
-40	0				
+40	0				0
 41	1	0.223279715	0.611168444	0.7103580388075188	1
 42	1	2.04505968	0.999095738	0.0013051645925104319	1
 43	1	0.169680834	0.56447953	0.82500683046719547	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.15510464	0.0109047387	0.015818618982627604	0
 137	0	-1.24130344	0.008020028	0.011617101215948859	0
 138	0	-1.0749054	0.0144998142	0.021071951694510416	0
-139	0				
+139	0				0
 140	0	-1.24130344	0.008020028	0.011617101215948859	0
 141	0	-1.28360271	0.00689550675	0.0099825705316781733	0
 142	1	0.643275	0.8769101	0.18949916409473391	1
 143	0	-0.8591082	0.0309929028	0.04542086264678518	0
 144	0	-1.23970342	0.008065961	0.011683906942824285	0
-145	0				
+145	0				0
 146	1	0.4436772	0.7764816	0.36497630408526505	1
 147	0	-1.13820457	0.01158053	0.016804665017851262	0
 148	0	-0.320714116	0.181648508	0.2892074628941344	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.9467714	0.9550218	0.066394431489110783	1
 156	0	-1.11830425	0.0124295028	0.018044356997620709	0
 157	0	-1.19580388	0.009433212	0.013673843835136703	0
-158	0				
+158	0				0
 159	1	2.5887537	0.9998721	0.0001845491876153846	1
 160	1	1.92586017	0.9986121	0.0020036987954509607	1
 161	0	-1.04420578	0.01616599	0.023513167231551696	0
 162	0	-1.15350461	0.0109670116	0.015909453114236246	0
 163	0	-1.00530624	0.0185497329	0.027012930786301039	0
-164	0				
+164	0				0
 165	0	-0.9275073	0.0243961066	0.035632579294711073	0
 166	1	2.06175947	0.9991484	0.0012290814661556479	1
 167	1	1.15397048	0.9781426	0.031883260676163518	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.0278829336	0.437610149	0.83035753638984611	1
 233	1	1.11616874	0.975037336	0.036470630963644925	1
 234	0	-0.544210553	0.09034561	0.13660958234622511	0
-235	0				
+235	0				0
 236	1	2.15735817	0.999396145	0.00087144125636392123	1
 237	1	1.37376881	0.9899692	0.014544463077068375	1
 238	1	2.659554	0.9999008	0.00014309666195095306	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.70435286	0.9999156	0.00012176885553963592	1
 247	1	0.616675138	0.8662006	0.207226880023576	1
 248	0	-0.7762085	0.04131975	0.060878383940094143	0
-249	0				
+249	0				0
 250	0	-1.16220379	0.0106326314	0.015421777653289784	0
 251	1	1.43526506	0.9919444	0.011668877043853167	1
 252	0	0.8921714	0.9457866	4.2052065773298537	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.6439743	0.8771814	0.18905285611569214	1
 273	1	-0.149016142	0.29164663	1.7777066932129042	0
 274	0	-1.08650517	0.0139153069	0.020216532376881539	0
-275	0				
+275	0				0
 276	0	-1.19740391	0.009379565	0.013595712679399167	0
 277	0	-1.28200269	0.00693504466	0.010040008870103924	0
 278	0	-1.23810339	0.008112156	0.01175109505221196	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.98086047	0.998861	0.0016441447437435472	1
 290	0	-1.32590222	0.005927712	0.0085773281383116576	0
 291	0	-1.23810339	0.008112156	0.01175109505221196	0
-292	1				
+292	1				0
 293	1	1.05756974	0.9693573	0.044899543967322132	1
-294	0				
+294	0				0
 295	1	1.67846322	0.9966264	0.0048753374261991068	1
 296	0	0.418977976	0.760678768	2.062979700875831	1
-297	0				
+297	0				0
 298	0	-0.865008354	0.0303616133	0.044481280497859745	0
 299	1	1.15566754	0.9782728	0.031691271742118471	1
 300	1	1.43996739	0.9920784	0.011473925159666753	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.7111747	0.9009488	0.15048293737780147	1
 313	0	-1.32590222	0.005927712	0.0085773281383116576	0
 314	0	-1.3091023	0.006294775	0.0091101437491470354	0
-315	0				
+315	0				0
 316	1	0.9520712	0.955833852	0.065168231187009498	1
 317	1	2.1167593	0.999301255	0.0010084286664473847	1
 318	0	-1.15680456	0.0108389612	0.015722679136914018	0
 319	0	0.43477726	0.7708744	2.1257893169799549	1
 320	1	1.20646763	0.9818366	0.026445122755562926	1
-321	0				
+321	0				0
 322	0	-1.15350461	0.0109670116	0.015909453114236246	0
 323	1	1.1870687	0.980549	0.028338400890888689	1
 324	0	-1.23810339	0.008112156	0.01175109505221196	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-0.775208354	0.0414625444	0.061093287384022553	0
 409	0	-1.11720467	0.0124781644	0.018115446186086449	0
 410	0	-1.28200269	0.00693504466	0.010040008870103924	0
-411	0				
+411	0				0
 412	1	1.89956212	0.9984746	0.0022023701778286324	1
 413	0	-0.9887064	0.01966903	0.028659194266170487	0
 414	1	1.3937664	0.9906591	0.013539378350893604	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.266803	0.00732205063	0.010602349145536318	0
 615	0	-0.994706035	0.0192570463	0.028053029788189736	0
 616	0	-1.19740391	0.009379565	0.013595712679399167	0
-617	0				
+617	0				0
 618	0	-1.15510464	0.0109047387	0.015818618982627604	0
 619	0	-1.11280513	0.0126747517	0.018402674010350579	0
 620	0	-1.19740391	0.009379565	0.013595712679399167	0
diff --git a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-TrainTest-breast-cancer.txt
index 29a93c0326..3f80a3624c 100644
--- a/test/BaselineOutput/SingleDebug/SGD/BinarySGD-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SGD/BinarySGD-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	0.822916269	0.694855034	0.52521607106152413	1
 21	1	1.02655149	0.736246765	0.441738705665011	1
 22	0	-1.01600647	0.265806019	0.44576680836978433	0
-23	1				
+23	1				0
 24	0	-1.03864312	0.261411875	0.43715802871945769	0
 25	1	0.184996247	0.5461176	0.87271643290195555	1
 26	0	-0.9708479	0.274711519	0.46337315957197994	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.7265403	0.325954378	0.56908185228017971	0
 38	1	0.933466434	0.717778	0.47839033548395937	1
 39	1	0.4073757	0.600458443	0.7358636922780708	1
-40	0				
+40	0				0
 41	1	0.04465425	0.5111617	0.96814839425710286	1
 42	1	1.43612671	0.8078541	0.30783330336923359	1
 43	1	0.0479370356	0.511981964	0.96583510643055481	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-0.9885073	0.271207035	0.45641906112335939	0
 137	0	-1.04836845	0.259538531	0.4335034307664255	0
 138	0	-0.9260764	0.283721417	0.48140728969854896	0
-139	0				
+139	0				0
 140	0	-1.04836845	0.259538531	0.4335034307664255	0
 141	0	-1.07586777	0.2542888	0.42331107075059288	0
 142	1	0.373193622	0.592230439	0.75576945149404562	1
 143	0	-0.7654944	0.317454576	0.55100303407297502	0
 144	0	-1.04350591	0.2604741	0.43532739229387868	0
-145	0				
+145	0				0
 146	1	0.2147963	0.553493559	0.85336156547352904	1
 147	0	-0.9662212	0.275634348	0.46520995753133637	0
 148	0	-0.318193555	0.421116054	0.78865394770237895	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.600466	0.6457629	0.63092349091318589	1
 156	0	-0.9430999	0.2802746	0.47448152072334643	0
 157	0	-1.01114392	0.266756058	0.44763484776839352	0
-158	0				
+158	0				0
 159	1	1.87013483	0.866473854	0.20677187910596315	1
 160	1	1.34225249	0.7928601	0.33486178660539723	1
 161	0	-0.901281357	0.288787246	0.49164689849299364	0
 162	0	-0.9836446	0.2721692	0.45832499621527728	0
 163	0	-0.855002642	0.2983845	0.51124744948014056	0
-164	0				
+164	0				0
 165	0	-0.8168132	0.306440562	0.5279085681868505	0
 166	1	1.49839211	0.817334533	0.29100140459599977	1
 167	1	0.8153703	0.6932527	0.5285468008024331	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.08038044	0.4799157	0.9431826305616432	0
 233	1	0.6980891	0.667763948	0.58258988829378422	1
 234	0	-0.49562943	0.378568321	0.68633230772699549	0
-235	0				
+235	0				0
 236	1	1.52862382	0.8218049	0.28313219549408758	1
 237	1	0.9843018	0.727960944	0.45806704440223556	1
 238	1	1.96605682	0.877186954	0.18904373922390869	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	1.97140193	0.8777616	0.18809893386755816	1
 247	1	0.323040724	0.580065131	0.78571319608569612	1
 248	0	-0.6818254	0.335854024	0.59042772056631165	0
-249	0				
+249	0				0
 250	0	-0.9754619	0.273793161	0.46154757804170599	0
 251	1	0.9712138	0.725361347	0.46322822535916075	1
 252	0	0.5616691	0.6368387	1.4613175226151991	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.354397058	0.587683439	0.76688885070680657	1
 273	1	-0.237432361	0.4409192	1.1814138244518058	0
 274	0	-0.9287806	0.28317216	0.48030142611403009	0
-275	0				
+275	0				0
 276	0	-1.01600647	0.265806019	0.44576680836978433	0
 277	0	-1.07100511	0.255211979	0.42509822607281988	0
 278	0	-1.03864312	0.261411875	0.43715802871945769	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.4364171	0.8078992	0.30775283385408775	1
 290	0	-1.10336709	0.249109536	0.4133256254437066	0
 291	0	-1.03864312	0.261411875	0.43715802871945769	0
-292	1				
+292	1				0
 293	1	0.6671076	0.6608552	0.59759395409472371	1
-294	0				
+294	0				0
 295	1	1.17509961	0.764065564	0.38823165513968877	1
 296	0	0.224430084	0.5558732	1.1709565135958244	1
-297	0				
+297	0				0
 298	0	-0.7844506	0.313361466	0.54237727145415437	0
 299	1	0.748945951	0.678949	0.55862488926125509	1
 300	1	1.01898217	0.7347743	0.44462694496525584	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.4770298	0.617046237	0.69654949630747753	1
 313	0	-1.10336709	0.249109536	0.4133256254437066	0
 314	0	-1.09132075	0.251369655	0.41767456748452503	0
-315	0				
+315	0				0
 316	1	0.5936177	0.6441948	0.63443112049115613	1
 317	1	1.53676748	0.8229943	0.28104567061447505	1
 318	0	-0.977696	0.2733492	0.46066585861057346	0
 319	0	0.228058934	0.5567689	1.1738689621124481	1
 320	1	0.7848048	0.6867147	0.54221722972478248	1
-321	0				
+321	0				0
 322	0	-0.9836446	0.2721692	0.45832499621527728	0
 323	1	0.799038649	0.6897688	0.53581523979313106	1
 324	0	-1.03864312	0.261411875	0.43715802871945769	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-0.6859037	0.334944934	0.58845429463916576	0
 409	0	-0.9535757	0.2781663	0.47026158367983178	0
 410	0	-1.07100511	0.255211979	0.42509822607281988	0
-411	0				
+411	0				0
 412	1	1.353524	0.794705153	0.331508396641091	1
 413	0	-0.8662151	0.296042472	0.50643970604072797	0
 414	1	0.9272311	0.7165132	0.48093477882048502	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.06382155	0.256579816	0.42775023737254403	0
 615	0	-0.863645554	0.296578258	0.50753816766843873	0
 616	0	-1.01600647	0.265806019	0.44576680836978433	0
-617	0				
+617	0				0
 618	0	-0.9885073	0.271207035	0.45641906112335939	0
 619	0	-0.961007953	0.276676446	0.46728696355201749	0
 620	0	-1.01600647	0.265806019	0.44576680836978433	0
diff --git a/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-CV-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-CV-breast-cancer.txt
index d0e7499c6d..5218dcbd4f 100644
--- a/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	454.251282	1	0	1
 35	0	-320.737427	0	0	0
 37	0	-78.9787	5.011722E-35	0	0
-40	0				
+40	0				0
 41	1	199.0091	1	0	1
 44	1	656.8247	1	0	1
 45	0	-322.804565	0	0	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-289.415222	0	0	0
 141	0	-344.61084	0	0	0
 144	0	-320.737427	0	0	0
-145	0				
+145	0				0
 147	0	-309.023651	0	0	0
 150	0	-272.79837	0	0	0
 151	1	249.55658	1	0	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-349.126221	0	0	0
 156	0	-227.212433	0	0	0
 161	0	-274.6302	0	0	0
-164	0				
+164	0				0
 167	1	283.316284	1	0	1
 169	0	-331.047241	0	0	0
 171	0	-301.379425	0	0	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	1044.54126	1	0	1
 247	1	409.237671	1	0	1
 248	0	-221.818024	0	0	0
-249	0				
+249	0				0
 250	0	-251.085815	0	0	0
 252	0	307.68988	1	Infinity	1
 254	1	728.536743	1	0	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-301.379425	0	0	0
 271	0	-283.3178	0	0	0
 272	1	408.017578	1	0	1
-275	0				
+275	0				0
 276	0	-316.222015	0	0	0
 277	0	-325.252838	0	0	0
 278	0	-301.379425	0	0	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-301.379425	0	0	0
 293	1	386.6949	1	0	1
 296	0	139.220642	1	Infinity	1
-297	0				
+297	0				0
 299	1	227.814941	1	0	1
 300	1	407.6792	1	0	1
 301	0	-301.379425	0	0	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	466.170166	1	0	1
 317	1	736.0132	1	0	1
 319	0	161.598083	1	Infinity	1
-321	0				
+321	0				0
 323	1	388.03302	1	0	1
 327	0	-325.252838	0	0	0
 328	1	584.984	1	0	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	1115.01685	1	0	1
 613	0	-169.23941	0	0	0
 614	0	-292.156342	0	0	0
-617	0				
+617	0				0
 618	0	-311.7066	0	0	0
 619	0	-307.1912	0	0	0
 621	0	-15.8763733	1.27344038E-07	1.8371862313930792E-07	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-643.057739	0	0	0
 19	0	-668.631836	0	0	0
 22	0	-540.900146	0	0	0
-23	1				
+23	1				0
 24	0	-604.696655	0	0	0
 26	0	-270.657074	0	0	0
 27	0	-566.4742	0	0	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-670.7141	0	0	0
 135	0	-421.652374	0	0	0
 136	0	-553.6872	0	0	0
-139	0				
+139	0				0
 140	0	-451.529541	0	0	0
 142	1	488.315338	1	0	1
 143	0	-142.331116	0	0	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-322.504425	0	0	0
 155	1	1089.60254	1	0	1
 157	0	-617.483643	0	0	0
-158	0				
+158	0				0
 159	1	1923.50525	1	0	1
 160	1	1494.5094	1	0	1
 162	0	-630.2707	0	0	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1347.16248	1	0	1
 232	0	355.92923	1	Infinity	1
 234	0	50.92752	1	Infinity	1
-235	0				
+235	0				0
 236	1	1204.77161	1	0	1
 238	1	2421.62354	1	0	1
 243	0	-499.813416	0	0	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	1933.38391	1	0	1
 287	0	-670.7141	0	0	0
 289	1	1586.01746	1	0	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	906.5393	1	0	1
 298	0	-764.4775	0	0	0
 302	1	1682.504	1	0	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-604.696655	0	0	0
 310	0	-657.927	0	0	0
 313	0	-425.9555	0	0	0
-315	0				
+315	0				0
 318	0	-994.1385	0	0	0
 320	1	276.6519	1	0	1
 322	0	-630.2707	0	0	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-515.32605	0	0	0
 408	0	-106.253662	0	0	0
 410	0	-515.32605	0	0	0
-411	0				
+411	0				0
 412	1	1142.7179	1	0	1
 417	0	-515.32605	0	0	0
 420	0	-151.036346	0	0	0
diff --git a/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-TrainTest-breast-cancer.txt
index f744bc3525..64a3a40edd 100644
--- a/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleDebug/SymSGD/SymSGD-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	10.1497192	0.9999609	5.6411412351548271E-05	1
 21	1	-61.521698	1.91190378E-27	88.757048641689195	0
 22	0	-407.94165	0	0	0
-23	1				
+23	1				0
 24	0	-413.829132	0	0	0
 25	1	-111.690765	0	Infinity	0
 26	0	-333.49762	0	0	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-367.9438	0	0	0
 38	1	125.049805	1	0	1
 39	1	-120.420319	0	Infinity	0
-40	0				
+40	0				0
 41	1	-214.114883	0	Infinity	0
 42	1	86.67383	1	0	1
 43	1	-299.954132	0	Infinity	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-408.326935	0	0	0
 137	0	-401.2836	0	0	0
 138	0	-411.7511	0	0	0
-139	0				
+139	0				0
 140	0	-401.2836	0	0	0
 141	0	-400.898315	0	0	0
 142	1	-108.134125	0	Infinity	0
 143	0	-305.7808	0	0	0
 144	0	-407.556366	0	0	0
-145	0				
+145	0				0
 146	1	-205.1228	0	Infinity	0
 147	0	-408.638123	0	0	0
 148	0	-448.917847	0	0	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	39.9500122	1	0	1
 156	0	-361.30127	0	0	0
 157	0	-414.214417	0	0	0
-158	0				
+158	0				0
 159	1	214.183228	1	0	1
 160	1	120.047485	1	0	1
 161	0	-401.219147	0	0	0
 162	0	-414.5997	0	0	0
 163	0	-282.1694	0	0	0
-164	0				
+164	0				0
 165	0	-377.536072	0	0	0
 166	1	123.761658	1	0	1
 167	1	-9.15014648	0.000106192965	13.201024182527696	0
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-256.504028	0	0	0
 233	1	-84.9973755	1.21929513E-37	122.62529213957316	0
 234	0	-275.7568	0	0	0
-235	0				
+235	0				0
 236	1	116.098267	1	0	1
 237	1	26.0986938	1	0	1
 238	1	370.027954	1	0	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	321.109131	1	0	1
 247	1	-61.9207153	1.28284749E-27	89.332708892981643	0
 248	0	-346.1557	0	0	0
-249	0				
+249	0				0
 250	0	-354.643219	0	0	0
 251	1	108.2807	1	0	1
 252	0	-4.193939	0.0148625113	0.021603009492489122	0
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	-151.574524	0	Infinity	0
 273	1	-303.688629	0	Infinity	0
 274	0	-400.833862	0	0	0
-275	0				
+275	0				0
 276	0	-407.94165	0	0	0
 277	0	-407.171082	0	0	0
 278	0	-413.829132	0	0	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	175.671082	1	0	1
 290	0	-400.513	0	0	0
 291	0	-413.829132	0	0	0
-292	1				
+292	1				0
 293	1	51.4936523	1	0	1
-294	0				
+294	0				0
 295	1	5.8543396	0.997140765	0.0041309123233919023	1
 296	0	-173.148254	0	0	0
-297	0				
+297	0				0
 298	0	-429.3664	0	0	0
 299	1	-112.8385	0	Infinity	0
 300	1	-114.377228	0	Infinity	0
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	-175.547363	0	Infinity	0
 313	0	-400.513	0	0	0
 314	0	-382.020966	0	0	0
-315	0				
+315	0				0
 316	1	-56.5515747	2.753995E-25	81.586676422594735	0
 317	1	168.155884	1	0	1
 318	0	-489.2794	0	0	0
 319	0	-232.038055	0	0	0
 320	1	16.8273315	0.99999994	8.5991327994145617E-08	1
-321	0				
+321	0				0
 322	0	-414.5997	0	0	0
 323	1	72.79901	1	0	1
 324	0	-413.829132	0	0	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-278.598877	0	0	0
 409	0	-411.365784	0	0	0
 410	0	-407.171082	0	0	0
-411	0				
+411	0				0
 412	1	21.296814	1	0	1
 413	0	-418.794434	0	0	0
 414	1	17.1500549	0.99999994	8.5991327994145617E-08	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-382.40625	0	0	0
 615	0	-415.175232	0	0	0
 616	0	-407.94165	0	0	0
-617	0				
+617	0				0
 618	0	-408.326935	0	0	0
 619	0	-408.712219	0	0	0
 620	0	-407.94165	0	0	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt
index eb8fd43aae..e3b32ab1be 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.PAVcalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	3.64133739	1	0	1
 35	0	-2.796535	1E-15	1.4415419267167138E-15	0
 37	0	-1.65404248	1E-15	1.4415419267167138E-15	0
-40	0				
+40	0				0
 41	1	1.04337406	0.8947368	0.16046469748481262	1
 44	1	4.33966541	1	0	1
 45	0	-2.89273548	1E-15	1.4415419267167138E-15	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-2.35179329	1E-15	1.4415419267167138E-15	0
 141	0	-2.904073	1E-15	1.4415419267167138E-15	0
 144	0	-2.796535	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 147	0	-2.463921	1E-15	1.4415419267167138E-15	0
 150	0	-2.8614285	1E-15	1.4415419267167138E-15	0
 151	1	3.17632246	1	0	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-3.01920986	1E-15	1.4415419267167138E-15	0
 156	0	-2.49565363	1E-15	1.4415419267167138E-15	0
 161	0	-2.30924	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 167	1	2.38255262	0.8947368	0.16046469748481262	1
 169	0	-3.03097248	1E-15	1.4415419267167138E-15	0
 171	0	-2.804134	1E-15	1.4415419267167138E-15	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	7.227234	1	0	1
 247	1	2.672493	0.8947368	0.16046469748481262	1
 248	0	-1.711307	1E-15	1.4415419267167138E-15	0
-249	0				
+249	0				0
 250	0	-2.60319138	1E-15	1.4415419267167138E-15	0
 252	0	2.992918	0.8947368	3.2479272984652883	1
 254	1	5.35164165	1	0	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-2.804134	1E-15	1.4415419267167138E-15	0
 271	0	-2.34358668	1E-15	1.4415419267167138E-15	0
 272	1	2.73419476	0.8947368	0.16046469748481262	1
-275	0				
+275	0				0
 276	0	-2.68139815	1E-15	1.4415419267167138E-15	0
 277	0	-2.91167164	1E-15	1.4415419267167138E-15	0
 278	0	-2.804134	1E-15	1.4415419267167138E-15	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-2.804134	1E-15	1.4415419267167138E-15	0
 293	1	3.413344	1	0	1
 296	0	1.47483253	0.8947368	3.2479272984652883	1
-297	0				
+297	0				0
 299	1	3.53376913	1	0	1
 300	1	3.78027344	1	0	1
 301	0	-2.804134	1E-15	1.4415419267167138E-15	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.45851088	1	0	1
 317	1	5.48386	1	0	1
 319	0	1.44604874	0.8947368	3.2479272984652883	1
-321	0				
+321	0				0
 323	1	3.36483288	1	0	1
 327	0	-2.91167164	1E-15	1.4415419267167138E-15	0
 328	1	3.03614	0.8947368	0.16046469748481262	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	8.167599	1	0	1
 613	0	-2.39343452	1E-15	1.4415419267167138E-15	0
 614	0	-2.85382986	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-2.56626129	1E-15	1.4415419267167138E-15	0
 619	0	-2.45112467	1E-15	1.4415419267167138E-15	0
 621	0	-0.5349846	0.2	0.32192810026182023	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-2.27471757	1E-15	1.4415419267167138E-15	0
 19	0	-2.00358748	1E-15	1.4415419267167138E-15	0
 22	0	-2.5426836	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-2.68141246	1E-15	1.4415419267167138E-15	0
 26	0	-2.33200574	1E-15	1.4415419267167138E-15	0
 27	0	-2.27155375	1E-15	1.4415419267167138E-15	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-2.546271	1E-15	1.4415419267167138E-15	0
 135	0	-1.52827668	1E-15	1.4415419267167138E-15	0
 136	0	-2.40711856	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-2.67508459	1E-15	1.4415419267167138E-15	0
 142	1	2.1587286	0.9117647	0.13326656969825684	1
 143	0	-1.54474568	1E-15	1.4415419267167138E-15	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.83878517	1E-15	1.4415419267167138E-15	0
 155	1	3.237853	0.9117647	0.13326656969825684	1
 157	0	-2.54584742	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	6.77223158	1	0	1
 160	1	5.42115831	1	0	1
 162	0	-2.41028237	1E-15	1.4415419267167138E-15	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.187345	1	0	1
 232	0	0.397937775	0.714285731	1.8073550080489322	1
 234	0	-1.183644	1E-15	1.4415419267167138E-15	0
-235	0				
+235	0				0
 236	1	5.6324296	1	0	1
 238	1	6.77774	1	0	1
 243	0	-1.01514125	1E-15	1.4415419267167138E-15	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	7.8132205	1	0	1
 287	0	-2.546271	1E-15	1.4415419267167138E-15	0
 289	1	5.25516939	1	0	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77293825	1	0	1
 298	0	-1.80093193	1E-15	1.4415419267167138E-15	0
 302	1	7.77011251	1	0	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-2.68141246	1E-15	1.4415419267167138E-15	0
 310	0	-2.68183613	1E-15	1.4415419267167138E-15	0
 313	0	-2.94621468	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 318	0	-2.69217515	1E-15	1.4415419267167138E-15	0
 320	1	3.800508	0.9444444	0.082462200658479604	1
 322	0	-2.41028237	1E-15	1.4415419267167138E-15	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.81381369	1E-15	1.4415419267167138E-15	0
 408	0	-1.46855927	1E-15	1.4415419267167138E-15	0
 410	0	-2.81381369	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	4.83788157	1	0	1
 417	0	-2.81381369	1E-15	1.4415419267167138E-15	0
 420	0	-1.04175115	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt
index 3b51cd60d5..31cb0b05b4 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.calibrateRandom.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	3.64133739	0.9844741	0.022574810341618422	1
 35	0	-2.796535	0.0199539755	0.029078592776682857	0
 37	0	-1.65404248	0.0782266259	0.11751599963260938	0
-40	0				
+40	0				0
 41	1	1.04337406	0.7116856	0.49068805388019454	1
 44	1	4.33966541	0.9934526	0.0094769477341525628	1
 45	0	-2.89273548	0.0177341755	0.025814589979333783	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-2.35179329	0.03427408	0.050314293386144675	0
 141	0	-2.904073	0.0174890943	0.025454673744601461	0
 144	0	-2.796535	0.0199539755	0.029078592776682857	0
-145	0				
+145	0				0
 147	0	-2.463921	0.0299276374	0.04383572570114834	0
 150	0	-2.8614285	0.01842858	0.026834852844454766	0
 151	1	3.17632246	0.9725775	0.040114860620962978	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-3.01920986	0.0151813291	0.022069981158425081	0
 156	0	-2.49565363	0.0287977811	0.042156377165560456	0
 161	0	-2.30924	0.0360781476	0.053011906638395674	0
-164	0				
+164	0				0
 167	1	2.38255262	0.9293544	0.10569919063924076	1
 169	0	-3.03097248	0.0149631584	0.021750410734051751	0
 171	0	-2.804134	0.0197691489	0.028806541052408416	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	7.227234	0.999821365	0.00025773902362411926	1
 247	1	2.672493	0.9497448	0.074388155670230882	1
 248	0	-1.711307	0.07322063	0.10970216917333013	0
-249	0				
+249	0				0
 250	0	-2.60319138	0.0252686124	0.036923393165046718	0
 252	0	2.992918	0.9657571	4.8680501214754637	1
 254	1	5.35164165	0.998142242	0.0026826702788205732	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-2.804134	0.0197691489	0.028806541052408416	0
 271	0	-2.34358668	0.0346150957	0.050823827322496622	0
 272	1	2.73419476	0.9532994	0.068998701675288501	1
-275	0				
+275	0				0
 276	0	-2.68139815	0.0229703225	0.033525709865030048	0
 277	0	-2.91167164	0.0173267	0.025216237008576704	0
 278	0	-2.804134	0.0197691489	0.028806541052408416	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-2.804134	0.0197691489	0.028806541052408416	0
 293	1	3.413344	0.9794621	0.029938444898768346	1
 296	0	1.47483253	0.8088676	2.3873555377194497	1
-297	0				
+297	0				0
 299	1	3.53376913	0.982280254	0.025793396317687449	1
 300	1	3.78027344	0.986915946	0.019000876915907086	1
 301	0	-2.804134	0.0197691489	0.028806541052408416	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.45851088	0.980567157	0.028311653515975352	1
 317	1	5.48386	0.9984247	0.0022744566762884174	1
 319	0	1.44604874	0.803245664	2.3455326626007635	1
-321	0				
+321	0				0
 323	1	3.36483288	0.978206754	0.031788669528507826	1
 327	0	-2.91167164	0.0173267	0.025216237008576704	0
 328	1	3.03614	0.9674988	0.047668253892284254	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	8.167599	0.9999448	7.9630164919418245E-05	1
 613	0	-2.39343452	0.03259308	0.047805235639227908	0
 614	0	-2.85382986	0.0186011065	0.027088450049153875	0
-617	0				
+617	0				0
 618	0	-2.56626129	0.02643034	0.038643886518904186	0
 619	0	-2.45112467	0.0303953178	0.044531429350354604	0
 621	0	-0.5349846	0.255690753	0.42602593625059765	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-2.27471757	0.0249303821	0.036422867055812318	0
 19	0	-2.00358748	0.03410183	0.050056992617068342	0
 22	0	-2.5426836	0.0182464458	0.026567179066779304	0
-23	1				
+23	1				0
 24	0	-2.68141246	0.015512228	0.022554807909292037	0
 26	0	-2.33200574	0.02332543	0.034050161954667077	0
 27	0	-2.27155375	0.0250220858	0.036558556406276949	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-2.546271	0.0181701127	0.026455011357386121	0
 135	0	-1.52827668	0.0585265532	0.087007689086403689	0
 136	0	-2.40711856	0.0213731956	0.031169296396687675	0
-139	0				
+139	0				0
 140	0	-2.67508459	0.015627671	0.022723991158114246	0
 142	1	2.1587286	0.83348304	0.26277525125659912	1
 143	0	-1.54474568	0.05745574	0.085367730161702821	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.83878517	0.0411879122	0.060679997683715341	0
 155	1	3.237853	0.947596252	0.077655602601770859	1
 157	0	-2.54584742	0.0181791112	0.026468233670711376	0
-158	0				
+158	0				0
 159	1	6.77223158	0.999177039	0.0011877710421138682	1
 160	1	5.42115831	0.995904	0.0059213730758132374	1
 162	0	-2.41028237	0.0212945715	0.031053393109467146	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.187345	0.9945968	0.0078163354020312284	1
 232	0	0.397937775	0.381006956	0.69200489802945642	1
 234	0	-1.183644	0.085664086	0.12920380666492423	0
-235	0				
+235	0				0
 236	1	5.6324296	0.9968118	0.0046069378176225089	1
 238	1	6.77774	0.9991824	0.0011800254692933552	1
 243	0	-1.01514125	0.102734588	0.15639329612707187	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	7.8132205	0.999761462	0.00034417833577817593	1
 287	0	-2.546271	0.0181701127	0.026455011357386121	0
 289	1	5.25516939	0.9950138	0.0072115986401722143	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77293825	0.9911819	0.012778237651616852	1
 298	0	-1.80093193	0.0430044457	0.063415872213561694	0
 302	1	7.77011251	0.999748945	0.00036224093577622284	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-2.68141246	0.015512228	0.022554807909292037	0
 310	0	-2.68183613	0.0155045288	0.022543525273161929	0
 313	0	-2.94621468	0.0113662509	0.016491938164477051	0
-315	0				
+315	0				0
 318	0	-2.69217515	0.0153178023	0.022269919361612874	0
 320	1	3.800508	0.9724724	0.040270746291192143	1
 322	0	-2.41028237	0.0212945715	0.031053393109467146	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.81381369	0.0132805621	0.019288165348886492	0
 408	0	-1.46855927	0.06256822	0.093214386421141548	0
 410	0	-2.81381369	0.0132805621	0.019288165348886492	0
-411	0				
+411	0				0
 412	1	4.83788157	0.991832554	0.011831516022545778	1
 417	0	-2.81381369	0.0132805621	0.019288165348886492	0
 420	0	-1.04175115	0.09985152	0.15176509864238413	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt
index 09a2fb9aa7..afd5a0dfc0 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.nocalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Assigned
 32	1	3.64133739	1
 35	0	-2.796535	0
 37	0	-1.65404248	0
-40	0		
+40	0		0
 41	1	1.04337406	1
 44	1	4.33966541	1
 45	0	-2.89273548	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Assigned
 138	0	-2.35179329	0
 141	0	-2.904073	0
 144	0	-2.796535	0
-145	0		
+145	0		0
 147	0	-2.463921	0
 150	0	-2.8614285	0
 151	1	3.17632246	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Assigned
 154	0	-3.01920986	0
 156	0	-2.49565363	0
 161	0	-2.30924	0
-164	0		
+164	0		0
 167	1	2.38255262	1
 169	0	-3.03097248	0
 171	0	-2.804134	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Assigned
 246	1	7.227234	1
 247	1	2.672493	1
 248	0	-1.711307	0
-249	0		
+249	0		0
 250	0	-2.60319138	0
 252	0	2.992918	1
 254	1	5.35164165	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Assigned
 269	0	-2.804134	0
 271	0	-2.34358668	0
 272	1	2.73419476	1
-275	0		
+275	0		0
 276	0	-2.68139815	0
 277	0	-2.91167164	0
 278	0	-2.804134	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Assigned
 291	0	-2.804134	0
 293	1	3.413344	1
 296	0	1.47483253	1
-297	0		
+297	0		0
 299	1	3.53376913	1
 300	1	3.78027344	1
 301	0	-2.804134	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Assigned
 316	1	3.45851088	1
 317	1	5.48386	1
 319	0	1.44604874	1
-321	0		
+321	0		0
 323	1	3.36483288	1
 327	0	-2.91167164	0
 328	1	3.03614	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Assigned
 612	1	8.167599	1
 613	0	-2.39343452	0
 614	0	-2.85382986	0
-617	0		
+617	0		0
 618	0	-2.56626129	0
 619	0	-2.45112467	0
 621	0	-0.5349846	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Assigned
 17	0	-2.27471757	0
 19	0	-2.00358748	0
 22	0	-2.5426836	0
-23	1		
+23	1		0
 24	0	-2.68141246	0
 26	0	-2.33200574	0
 27	0	-2.27155375	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Assigned
 134	0	-2.546271	0
 135	0	-1.52827668	0
 136	0	-2.40711856	0
-139	0		
+139	0		0
 140	0	-2.67508459	0
 142	1	2.1587286	1
 143	0	-1.54474568	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Assigned
 153	0	-1.83878517	0
 155	1	3.237853	1
 157	0	-2.54584742	0
-158	0		
+158	0		0
 159	1	6.77223158	1
 160	1	5.42115831	1
 162	0	-2.41028237	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Assigned
 231	1	5.187345	1
 232	0	0.397937775	1
 234	0	-1.183644	0
-235	0		
+235	0		0
 236	1	5.6324296	1
 238	1	6.77774	1
 243	0	-1.01514125	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Assigned
 286	1	7.8132205	1
 287	0	-2.546271	0
 289	1	5.25516939	1
-292	1		
-294	0		
+292	1		0
+294	0		0
 295	1	4.77293825	1
 298	0	-1.80093193	0
 302	1	7.77011251	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Assigned
 307	0	-2.68141246	0
 310	0	-2.68183613	0
 313	0	-2.94621468	0
-315	0		
+315	0		0
 318	0	-2.69217515	0
 320	1	3.800508	1
 322	0	-2.41028237	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Assigned
 407	0	-2.81381369	0
 408	0	-1.46855927	0
 410	0	-2.81381369	0
-411	0		
+411	0		0
 412	1	4.83788157	1
 417	0	-2.81381369	0
 420	0	-1.04175115	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt
index 693440edc2..09ce4b3736 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	2.35438	0.996385	0.0052248235129257635	1
 35	0	-1.83556986	0.00724350661	0.010488202773633042	0
 37	0	-0.8828192	0.07420456	0.11123463299619094	0
-40	0				
+40	0				0
 41	1	0.6366718	0.7855496	0.34822575879653411	1
 44	1	2.72072053	0.998558342	0.002081372862402793	1
 45	0	-1.87994158	0.00648348359	0.0093841435784006184	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.51871562	0.0159320254	0.02317012154973026	0
 141	0	-1.93865037	0.00559835136	0.0080994066187532153	0
 144	0	-1.83556986	0.00724350661	0.010488202773633042	0
-145	0				
+145	0				0
 147	0	-1.69274938	0.010342177	0.014998299390129487	0
 150	0	-1.91297352	0.00596963847	0.0086381769438633477	0
 151	1	1.55168462	0.973401248	0.038893469912665984	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-2.0423522	0.004318493	0.0062437599081359638	0
 156	0	-1.73049688	0.009414184	0.013646131293487658	0
 161	0	-1.46562588	0.0181668717	0.026450249055215744	0
-164	0				
+164	0				0
 167	1	2.31870866	0.99604696	0.0057143326416850991	1
 169	0	-2.041339	0.00432946626	0.0062596597963016712	0
 171	0	-1.8361913	0.00723227439	0.010471879968765333	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	3.8998096	0.9999256	0.00010732116581602008	1
 247	1	0.9928844	0.8997386	0.15242216136874395	1
 248	0	-1.22778583	0.03256034	0.047756414470681303	0
-249	0				
+249	0				0
 250	0	-1.83357728	0.00727963867	0.010540711608751351	0
 252	0	1.37199	0.958826959	4.6021561858199664	1
 254	1	2.79375386	0.9988	0.0017323029622904203	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.8361913	0.00723227439	0.010471879968765333	0
 271	0	-1.42138422	0.0202620383	0.02953215377914243	0
 272	1	1.10222125	0.921965	0.11721610663727763	1
-275	0				
+275	0				0
 276	0	-1.73186815	0.009382072	0.013599363941350218	0
 277	0	-1.93927169	0.00558965746	0.0080867934194779039	0
 278	0	-1.8361913	0.00723227439	0.010471879968765333	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.8361913	0.00723227439	0.010471879968765333	0
 293	1	1.65592456	0.9794098	0.030015442677317709	1
 296	0	0.553571463	0.748245	1.9899076684215853	1
-297	0				
+297	0				0
 299	1	2.001486	0.991262555	0.012660861084033199	1
 300	1	2.09417748	0.9930671	0.010036913891508983	1
 301	0	-1.8361913	0.00723227439	0.010471879968765333	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	1.47151637	0.9676506	0.047441894201880302	1
 317	1	3.06524873	0.999393463	0.00087531320929783803	1
 319	0	0.8519552	0.8629285	2.8669995609516308	1
-321	0				
+321	0				0
 323	1	1.75474	0.9838682	0.023463058122578043	1
 327	0	-1.93927169	0.00558965746	0.0080867934194779039	0
 328	1	1.43182349	0.964374959	0.052333903838185522	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	5.09431458	0.9999963	5.3314720279485219E-06	1
 613	0	-1.63692176	0.0118829105	0.017246087060301379	0
 614	0	-1.9123522	0.00597891957	0.0086516472088849234	0
-617	0				
+617	0				0
 618	0	-1.62816632	0.0121443039	0.017627783540922228	0
 619	0	-1.52446461	0.0157068819	0.022840087163427197	0
 621	0	-0.188778639	0.31474337	0.54528371301135603	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.57970572	0.0144622317	0.021016934775320784	0
 19	0	-1.32506859	0.0253080986	0.036981837697027814	0
 22	0	-1.76987159	0.009491567	0.01375883626140059	0
-23	1				
+23	1				0
 24	0	-1.96166122	0.00619609	0.0089668769102733102	0
 26	0	-1.67495286	0.0117150256	0.017000988488892345	0
 27	0	-1.51523459	0.0166727714	0.024256502854015347	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.75784481	0.009748338	0.014132877086598956	0
 135	0	-1.07198834	0.04377895	0.06458392745656516	0
 136	0	-1.64255309	0.0125861792	0.018273256294688772	0
-139	0				
+139	0				0
 140	0	-1.832719	0.008254912	0.01195874763978641	0
 142	1	1.20702124	0.8832422	0.17911900782229345	1
 143	0	-1.436229	0.0198381469	0.028908095216224419	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.37983692	0.0224505328	0.032758385480089913	0
 155	1	1.24272728	0.8912444	0.16610696969487637	1
 157	0	-1.83434272	0.008225175	0.011915489581813862	0
-158	0				
+158	0				0
 159	1	4.09360933	0.999795	0.00029575448112624953	1
 160	1	3.04705143	0.997864842	0.0030836744978663621	1
 162	0	-1.70702422	0.0109114433	0.015828398337213719	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	2.80366325	0.996321738	0.0053163942348769758	1
 232	0	0.248882532	0.46910888	0.91351208341864276	1
 234	0	-0.8223932	0.0741594	0.11116426368346338	0
-235	0				
+235	0				0
 236	1	3.65436459	0.999451637	0.00079133718371403176	1
 238	1	4.208801	0.99984163	0.00022849704563499302	1
 243	0	-1.18483961	0.0343320966	0.050400968413634589	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	4.869809	0.999964	5.1939695512002597E-05	1
 287	0	-1.75784481	0.009748338	0.014132877086598956	0
 289	1	2.8387928	0.996599257	0.0049145964567919058	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	2.21859837	0.9864867	0.019628533461458434	1
 298	0	-1.053101	0.0455854833	0.067312108231381534	0
 302	1	4.847371	0.999962151	5.4605525036338512E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.96166122	0.00619609	0.0089668769102733102	0
 310	0	-1.88516331	0.007346285	0.010637570327263628	0
 313	0	-2.087356	0.00468213623	0.0067707579292392971	0
-315	0				
+315	0				0
 318	0	-1.9255811	0.006714394	0.00971948958962956	0
 320	1	1.98424911	0.9773634	0.03303300364958086	1
 322	0	-1.70702422	0.0109114433	0.015828398337213719	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.02450848	0.00538646942	0.0077920373965741406	0
 408	0	-1.276682	0.0281251986	0.041157619505191562	0
 410	0	-2.02450848	0.00538646942	0.0077920373965741406	0
-411	0				
+411	0				0
 412	1	2.820312	0.996455967	0.0051220399276606741	1
 417	0	-2.02450848	0.00538646942	0.0077920373965741406	0
 420	0	-1.02720916	0.0481775925	0.071235676455785449	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt
index 0c2f376b8f..a617fa7a4c 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.PAVcalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	4.309107	0.9756098	0.035623875334191583	1
 21	1	6.161626	1	0	1
 22	0	-3.35177135	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-3.57612	1E-15	1.4415419267167138E-15	0
 25	1	1.68778992	0.8125	0.29956028185890782	1
 26	0	-3.21128821	1E-15	1.4415419267167138E-15	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.20465565	0.0625	0.093109404391481479	0
 38	1	4.3035	0.9756098	0.035623875334191583	1
 39	1	2.444232	0.84	0.25153881203904033	1
-40	0				
+40	0				0
 41	1	2.349327	0.84	0.25153881203904033	1
 42	1	6.69547653	1	0	1
 43	1	0.1725626	0.7777778	0.36257005481575838	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-3.11112714	1E-15	1.4415419267167138E-15	0
 137	0	-3.60871148	1E-15	1.4415419267167138E-15	0
 138	0	-2.89319158	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-3.60871148	1E-15	1.4415419267167138E-15	0
 141	0	-3.8493557	1E-15	1.4415419267167138E-15	0
 142	1	2.848053	0.84	0.25153881203904033	1
 143	0	-2.73937	1E-15	1.4415419267167138E-15	0
 144	0	-3.59241557	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 146	1	1.31008816	0.8125	0.29956028185890782	1
 147	0	-3.43885779	1E-15	1.4415419267167138E-15	0
 148	0	-0.152019978	0.4	0.73696560849809378	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.618639	0.84	0.25153881203904033	1
 156	0	-3.41809654	1E-15	1.4415419267167138E-15	0
 157	0	-3.33547568	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	9.536341	1	0	1
 160	1	6.860572	1	0	1
 161	0	-2.5829134	1E-15	1.4415419267167138E-15	0
 162	0	-3.09483147	1E-15	1.4415419267167138E-15	0
 163	0	-2.50633955	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 165	0	-2.245256	1E-15	1.4415419267167138E-15	0
 166	1	6.456311	1	0	1
 167	1	4.319108	0.9756098	0.035623875334191583	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.8359299	0.7777778	2.1699250874336404	1
 233	1	3.89948845	0.9411765	0.087462835875881578	1
 234	0	-1.06992626	0.0625	0.093109404391481479	0
-235	0				
+235	0				0
 236	1	8.428113	1	0	1
 237	1	5.33226967	1	0	1
 238	1	9.183852	1	0	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.645902	1	0	1
 247	1	2.597087	0.84	0.25153881203904033	1
 248	0	-1.497818	0.0625	0.093109404391481479	0
-249	0				
+249	0				0
 250	0	-3.67503667	1E-15	1.4415419267167138E-15	0
 251	1	5.0781126	1	0	1
 252	0	3.308917	0.84	2.643855953298599	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	2.38956165	0.84	0.25153881203904033	1
 273	1	0.3306446	0.7777778	0.36257005481575838	1
 274	0	-2.82355762	1E-15	1.4415419267167138E-15	0
-275	0				
+275	0				0
 276	0	-3.35177135	1E-15	1.4415419267167138E-15	0
 277	0	-3.83305979	1E-15	1.4415419267167138E-15	0
 278	0	-3.57612	1E-15	1.4415419267167138E-15	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	6.52714539	1	0	1
 290	0	-4.08999968	1E-15	1.4415419267167138E-15	0
 291	0	-3.57612	1E-15	1.4415419267167138E-15	0
-292	1				
+292	1				0
 293	1	3.63595963	0.9411765	0.087462835875881578	1
-294	0				
+294	0				0
 295	1	5.25647163	1	0	1
 296	0	1.97336864	0.8125	2.4150374992788439	1
-297	0				
+297	0				0
 298	0	-2.03882861	1E-15	1.4415419267167138E-15	0
 299	1	4.99616432	1	0	1
 300	1	5.63767242	1	0	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.14314938	0.84	0.25153881203904033	1
 313	0	-4.08999968	1E-15	1.4415419267167138E-15	0
 314	0	-3.88960457	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 316	1	3.149722	0.84	0.25153881203904033	1
 317	1	7.02619457	1	0	1
 318	0	-3.406486	1E-15	1.4415419267167138E-15	0
 319	0	1.82393885	0.8125	2.4150374992788439	1
 320	1	5.15885925	1	0	1
-321	0				
+321	0				0
 322	0	-3.09483147	1E-15	1.4415419267167138E-15	0
 323	1	3.22143555	0.84	0.25153881203904033	1
 324	0	-3.57612	1E-15	1.4415419267167138E-15	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-2.29045367	1E-15	1.4415419267167138E-15	0
 409	0	-3.13383579	1E-15	1.4415419267167138E-15	0
 410	0	-3.83305979	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	6.52325153	1	0	1
 413	0	-2.39560747	1E-15	1.4415419267167138E-15	0
 414	1	5.304202	1	0	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-3.64896035	1E-15	1.4415419267167138E-15	0
 615	0	-2.675256	1E-15	1.4415419267167138E-15	0
 616	0	-3.35177135	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-3.11112714	1E-15	1.4415419267167138E-15	0
 619	0	-2.870483	1E-15	1.4415419267167138E-15	0
 620	0	-3.35177135	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt
index 69424d1f96..8822aa3d2f 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.calibrateRandom.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	4.309107	0.982883155	0.024908174987257281	1
 21	1	6.161626	0.997486651	0.0036305605660221312	1
 22	0	-3.35177135	0.0190011337	0.027676625763894382	0
-23	1				
+23	1				0
 24	0	-3.57612	0.0150948567	0.021943310344814629	0
 25	1	1.68778992	0.7883411	0.34310809466132391	1
 26	0	-3.21128821	0.02193545	0.031998411900987428	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.20465565	0.154014841	0.24129573984468006	0
 38	1	4.3035	0.98278445	0.025053063812451211	1
 39	1	2.444232	0.8913242	0.16597778265246793	1
-40	0				
+40	0				0
 41	1	2.349327	0.881352544	0.18220887767190111	1
 42	1	6.69547653	0.99855864	0.002080942285094773	1
 43	1	0.1725626	0.43382585	1.2048120730945795	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-3.11112714	0.0242936034	0.035481008429150813	0
 137	0	-3.60871148	0.0145974671	0.021214914966477344	0
 138	0	-2.89319158	0.0303093083	0.044403459692558656	0
-139	0				
+139	0				0
 140	0	-3.60871148	0.0145974671	0.021214914966477344	0
 141	0	-3.8493557	0.01139268	0.016530506138550251	0
 142	1	2.848053	0.9259271	0.11102947905485054	1
 143	0	-2.73937	0.0353999846	0.051997261707361145	0
 144	0	-3.59241557	0.0148441121	0.021576064827714625	0
-145	0				
+145	0				0
 146	1	1.31008816	0.7152061	0.48356908051152397	1
 147	0	-3.43885779	0.01737916	0.025293256640113757	0
 148	0	-0.152019978	0.353206038	0.62862188502856431	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.618639	0.9077395	0.139649725798073	1
 156	0	-3.41809654	0.0177530367	0.025842292400220613	0
 157	0	-3.33547568	0.01932072	0.028146699492868216	0
-158	0				
+158	0				0
 159	1	9.536341	0.999925554	0.0001074071635410925	1
 160	1	6.860572	0.998786449	0.0017518465781146784	1
 161	0	-2.5829134	0.0414183028	0.061026700952795158	0
 162	0	-3.09483147	0.0246999636	0.036081984337152172	0
 163	0	-2.50633955	0.04470976	0.065988970965053517	0
-164	0				
+164	0				0
 165	0	-2.245256	0.0579013154	0.086049905177797967	0
 166	1	6.456311	0.998150766	0.0026703506849678977	1
 167	1	4.319108	0.983057857	0.024651767929287045	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.8359299	0.6049175	1.3397742465159499	1
 233	1	3.89948845	0.9739913	0.038019246409892023	1
 234	0	-1.06992626	0.17323719	0.27445460033191865	0
-235	0				
+235	0				0
 236	1	8.428113	0.99976337	0.0003414259594434771	1
 237	1	5.33226967	0.994048536	0.0086117997569089607	1
 238	1	9.183852	0.9998925	0.00015513669190214178	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.645902	0.9998115	0.00027201620468366962	1
 247	1	2.597087	0.9058386	0.14267406349976108	1
 248	0	-1.497818	0.118221387	0.1815116096306757	0
-249	0				
+249	0				0
 250	0	-3.67503667	0.0136346063	0.019805910679898876	0
 251	1	5.0781126	0.9922549	0.011217294571842519	1
 252	0	3.308917	0.952875	4.4073641261174119	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	2.38956165	0.8856733	0.17515349285073656	1
 273	1	0.3306446	0.474698573	1.0749163809587898	1
 274	0	-2.82355762	0.0325194858	0.047695490325124906	0
-275	0				
+275	0				0
 276	0	-3.35177135	0.0190011337	0.027676625763894382	0
 277	0	-3.83305979	0.0115858121	0.016812375308683684	0
 278	0	-3.57612	0.0150948567	0.021943310344814629	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	6.52714539	0.9982823	0.0024802287545360943	1
 290	0	-4.08999968	0.008885143	0.012875839136462838	0
 291	0	-3.57612	0.0150948567	0.021943310344814629	0
-292	1				
+292	1				0
 293	1	3.63595963	0.9660381	0.049847993866089353	1
-294	0				
+294	0				0
 295	1	5.25647163	0.9935618	0.0093183820918222807	1
 296	0	1.97336864	0.8338234	2.589210701355853	1
-297	0				
+297	0				0
 298	0	-2.03882861	0.0708337	0.10599126176574966	0
 299	1	4.99616432	0.9915693	0.012214518276517204	1
 300	1	5.63767242	0.995665669	0.0062667080268442431	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.14314938	0.856945038	0.22272541817603111	1
 313	0	-4.08999968	0.008885143	0.012875839136462838	0
 314	0	-3.88960457	0.0109292	0.015854298528928425	0
-315	0				
+315	0				0
 316	1	3.149722	0.9448283	0.081875960094708669	1
 317	1	7.02619457	0.9989789	0.0014738699989607148	1
 318	0	-3.406486	0.0179655552	0.026154467003641695	0
 319	0	1.82393885	0.8110785	2.4041411141982105	1
 320	1	5.15885925	0.992876351	0.01031403381058839	1
-321	0				
+321	0				0
 322	0	-3.09483147	0.0246999636	0.036081984337152172	0
 323	1	3.22143555	0.948601961	0.076125243844936963	1
 324	0	-3.57612	0.0150948567	0.021943310344814629	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-2.29045367	0.05538148	0.082196274856991033	0
 409	0	-3.13383579	0.0237381756	0.034659977772739645	0
 410	0	-3.83305979	0.0115858121	0.016812375308683684	0
-411	0				
+411	0				0
 412	1	6.52325153	0.99827534	0.0024903070861691909	1
 413	0	-2.39560747	0.0499131419	0.073868682437534181	0
 414	1	5.304202	0.9938727	0.0088670155127870496	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-3.64896035	0.0140054561	0.020348431589167357	0
 615	0	-2.675256	0.0377570055	0.055526832252899339	0
 616	0	-3.35177135	0.0190011337	0.027676625763894382	0
-617	0				
+617	0				0
 618	0	-3.11112714	0.0242936034	0.035481008429150813	0
 619	0	-2.870483	0.0310136	0.045451678527033197	0
 620	0	-3.35177135	0.0190011337	0.027676625763894382	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt
index 0f08e7f566..29fbed5bf7 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.nocalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Assigned
 20	1	4.309107	1
 21	1	6.161626	1
 22	0	-3.35177135	0
-23	1		
+23	1		0
 24	0	-3.57612	0
 25	1	1.68778992	1
 26	0	-3.21128821	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Assigned
 37	0	-1.20465565	0
 38	1	4.3035	1
 39	1	2.444232	1
-40	0		
+40	0		0
 41	1	2.349327	1
 42	1	6.69547653	1
 43	1	0.1725626	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Assigned
 136	0	-3.11112714	0
 137	0	-3.60871148	0
 138	0	-2.89319158	0
-139	0		
+139	0		0
 140	0	-3.60871148	0
 141	0	-3.8493557	0
 142	1	2.848053	1
 143	0	-2.73937	0
 144	0	-3.59241557	0
-145	0		
+145	0		0
 146	1	1.31008816	1
 147	0	-3.43885779	0
 148	0	-0.152019978	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Assigned
 155	1	2.618639	1
 156	0	-3.41809654	0
 157	0	-3.33547568	0
-158	0		
+158	0		0
 159	1	9.536341	1
 160	1	6.860572	1
 161	0	-2.5829134	0
 162	0	-3.09483147	0
 163	0	-2.50633955	0
-164	0		
+164	0		0
 165	0	-2.245256	0
 166	1	6.456311	1
 167	1	4.319108	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Assigned
 232	0	0.8359299	1
 233	1	3.89948845	1
 234	0	-1.06992626	0
-235	0		
+235	0		0
 236	1	8.428113	1
 237	1	5.33226967	1
 238	1	9.183852	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Assigned
 246	1	8.645902	1
 247	1	2.597087	1
 248	0	-1.497818	0
-249	0		
+249	0		0
 250	0	-3.67503667	0
 251	1	5.0781126	1
 252	0	3.308917	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Assigned
 272	1	2.38956165	1
 273	1	0.3306446	1
 274	0	-2.82355762	0
-275	0		
+275	0		0
 276	0	-3.35177135	0
 277	0	-3.83305979	0
 278	0	-3.57612	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Assigned
 289	1	6.52714539	1
 290	0	-4.08999968	0
 291	0	-3.57612	0
-292	1		
+292	1		0
 293	1	3.63595963	1
-294	0		
+294	0		0
 295	1	5.25647163	1
 296	0	1.97336864	1
-297	0		
+297	0		0
 298	0	-2.03882861	0
 299	1	4.99616432	1
 300	1	5.63767242	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Assigned
 312	1	2.14314938	1
 313	0	-4.08999968	0
 314	0	-3.88960457	0
-315	0		
+315	0		0
 316	1	3.149722	1
 317	1	7.02619457	1
 318	0	-3.406486	0
 319	0	1.82393885	1
 320	1	5.15885925	1
-321	0		
+321	0		0
 322	0	-3.09483147	0
 323	1	3.22143555	1
 324	0	-3.57612	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Assigned
 408	0	-2.29045367	0
 409	0	-3.13383579	0
 410	0	-3.83305979	0
-411	0		
+411	0		0
 412	1	6.52325153	1
 413	0	-2.39560747	0
 414	1	5.304202	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Assigned
 614	0	-3.64896035	0
 615	0	-2.675256	0
 616	0	-3.35177135	0
-617	0		
+617	0		0
 618	0	-3.11112714	0
 619	0	-2.870483	0
 620	0	-3.35177135	0
diff --git a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt
index f1da00a926..4aafe56872 100644
--- a/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/AveragedPerceptron/AveragedPerceptron-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	2.27614474	0.99046284	0.01382524609823586	1
 21	1	2.71551442	0.9964734	0.0050968413754289565	1
 22	0	-1.91610467	0.007339344	0.010627482294138626	0
-23	1				
+23	1				0
 24	0	-2.12083673	0.00461633364	0.0066753814217522627	0
 25	1	0.579404354	0.6851912	0.54542144241146051	1
 26	0	-1.88108075	0.007944072	0.011506638331166432	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.9763708	0.0591678135	0.087990678318914578	0
 38	1	1.97923112	0.9814142	0.027065950749429996	1
 39	1	0.8320954	0.794680536	0.33155308613045453	1
-40	0				
+40	0				0
 41	1	0.88030076	0.812019646	0.30041346219868831	1
 42	1	3.29876113	0.9990636	0.0013515566126819322	1
 43	1	0.21289444	0.485705882	1.0418451361573347	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.76776826	0.010259659	0.014878012048023576	0
 137	0	-2.00804472	0.00596073642	0.0086252569347725905	0
 138	0	-1.64871967	0.0134130223	0.019481850015569589	0
-139	0				
+139	0				0
 140	0	-2.00804472	0.00596073642	0.0086252569347725905	0
 141	0	-2.15638113	0.00425880356	0.0061572754121802442	0
 142	1	1.42587113	0.93738085	0.093292772480968233	1
 143	0	-1.57122457	0.0159614533	0.023213265078036949	0
 144	0	-2.06444073	0.005245867	0.007588107121760313	0
-145	0				
+145	0				0
 146	1	0.5954063	0.693000734	0.52907121478369279	1
 147	0	-1.97373641	0.00644216966	0.0093241524569279595	0
 148	0	-0.5180371	0.15157719	0.23714468564136862	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	1.38289	0.931381464	0.10255592440494538	1
 156	0	-2.00303721	0.00602870947	0.0087239127220832425	0
 157	0	-1.97250068	0.00646021264	0.0093503519898618208	0
-158	0				
+158	0				0
 159	1	4.52930737	0.9999432	8.1952060728897203E-05	1
 160	1	3.334266	0.9991363	0.0012465526889135054	1
 161	0	-1.5841018	0.015507183	0.022547414886151074	0
 162	0	-1.82416427	0.009033906	0.01309239897866022	0
 163	0	-1.37575865	0.0246935654	0.03607251996647886	0
-164	0				
+164	0				0
 165	0	-1.40072858	0.0233600326	0.034101275741716536	0
 166	1	3.14331079	0.9986662	0.0019255122730899305	1
 167	1	2.61804938	0.995600462	0.0063611951559849299	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.262052536	0.5136946	1.0400654369740645	1
 233	1	2.16407657	0.987723053	0.017821513393369265	1
 234	0	-1.00943446	0.0551115535	0.081784080061402753	0
-235	0				
+235	0				0
 236	1	4.29103756	0.999902248	0.00014103266690546063	1
 237	1	2.42226958	0.9931447	0.0099241759578403005	1
 238	1	4.649124	0.9999568	6.2345058017421014E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	4.143937	0.9998633	0.00019719158494834585	1
 247	1	1.19717526	0.898898065	0.15377057127992425	1
 248	0	-1.217197	0.03506021	0.051489167959956395	0
-249	0				
+249	0				0
 250	0	-2.09497738	0.004895074	0.0070794400974987601	0
 251	1	2.700413	0.9963504	0.0052748803033137396	1
 252	0	1.58717227	0.955785036	4.4993214783146023	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.980280161	0.8443483	0.2440898311411345	1
 273	1	0.00625777245	0.3710024	1.4304995524008379	1
 274	0	-1.73243809	0.0111099789	0.01611801356385726	0
-275	0				
+275	0				0
 276	0	-1.91610467	0.007339344	0.010627482294138626	0
 277	0	-2.21277714	0.00374727719	0.0054163328257276827	0
 278	0	-2.12083673	0.00461633364	0.0066753814217522627	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	3.0956676	0.9985136	0.002146047033326764	1
 290	0	-2.30471754	0.00304132653	0.0043943924919565489	0
 291	0	-2.12083673	0.00461633364	0.0066753814217522627	0
-292	1				
+292	1				0
 293	1	1.9506762	0.980189741	0.028867048302480647	1
-294	0				
+294	0				0
 295	1	2.57708764	0.995172262	0.0069818201865888847	1
 296	0	0.6443205	0.7161847	1.8169756066019795	1
-297	0				
+297	0				0
 298	0	-1.00866961	0.0552023575	0.081922729978655878	0
 299	1	2.32091022	0.9913795	0.012490669010981763	1
 300	1	2.40809751	0.992921352	0.010248646031556275	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	1.19807649	0.899084449	0.15347146394878203	1
 313	0	-2.30471754	0.00304132653	0.0043943924919565489	0
 314	0	-2.26844478	0.00330244377	0.0047723037303054865	0
-315	0				
+315	0				0
 316	1	1.47730184	0.943915665	0.083270128208594502	1
 317	1	3.18132329	0.998776734	0.0017658802629188005	1
 318	0	-1.9538343	0.00673895236	0.0097551599741469968	0
 319	0	0.68000555	0.732414246	1.9019267823886503	1
 320	1	2.448116	0.993534148	0.009358541174187586	1
-321	0				
+321	0				0
 322	0	-1.82416427	0.009033906	0.01309239897866022	0
 323	1	1.739836	0.9683619	0.046381755881038968	1
 324	0	-2.12083673	0.00461633364	0.0066753814217522627	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-1.41561711	0.022598628	0.032976965091470092	0
 409	0	-1.79705584	0.009603847	0.013922383925987339	0
 410	0	-2.21277714	0.00374727719	0.0054163328257276827	0
-411	0				
+411	0				0
 412	1	3.177976	0.9987674	0.0017793974994358322	1
 413	0	-1.40844309	0.0229624342	0.033514061939899156	0
 414	1	2.38908362	0.992610335	0.010700618410080708	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-2.1201086	0.00462396163	0.0066864373761273176	0
 615	0	-1.529671	0.01751844	0.025497765300806271	0
 616	0	-1.91610467	0.007339344	0.010627482294138626	0
-617	0				
+617	0				0
 618	0	-1.76776826	0.010259659	0.014878012048023576	0
 619	0	-1.61943209	0.0143251875	0.020816334525491278	0
 620	0	-1.91610467	0.007339344	0.010627482294138626	0
diff --git a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt
index b337fd78da..d1bbf5dfc5 100644
--- a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.PAVcalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	1.25826859	1	0	1
 35	0	-1.41764426	1E-15	1.4415419267167138E-15	0
 37	0	-0.835641861	1E-15	1.4415419267167138E-15	0
-40	0				
+40	0				0
 41	1	0.227130175	0.8666667	0.20645086423799175	1
 44	1	1.61423349	1	0	1
 45	0	-1.47288513	1E-15	1.4415419267167138E-15	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.19960022	1E-15	1.4415419267167138E-15	0
 141	0	-1.47188914	1E-15	1.4415419267167138E-15	0
 144	0	-1.41764426	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 147	0	-1.334388	1E-15	1.4415419267167138E-15	0
 150	0	-1.48176765	1E-15	1.4415419267167138E-15	0
 151	1	0.7797704	1	0	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-1.54539037	1E-15	1.4415419267167138E-15	0
 156	0	-1.35846376	1E-15	1.4415419267167138E-15	0
 161	0	-1.1599288	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 167	1	1.07981849	1	0	1
 169	0	-1.5413084	1E-15	1.4415419267167138E-15	0
 171	0	-1.43690062	1E-15	1.4415419267167138E-15	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.368261	1	0	1
 247	1	0.4837153	0.8666667	0.20645086423799175	1
 248	0	-0.934056163	1E-15	1.4415419267167138E-15	0
-249	0				
+249	0				0
 250	0	-1.41270852	1E-15	1.4415419267167138E-15	0
 252	0	0.706041336	0.8666667	2.9068906815998465	1
 254	1	1.600352	1	0	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.43690062	1E-15	1.4415419267167138E-15	0
 271	0	-1.1428957	1E-15	1.4415419267167138E-15	0
 272	1	0.435359716	0.8666667	0.20645086423799175	1
-275	0				
+275	0				0
 276	0	-1.34414315	1E-15	1.4415419267167138E-15	0
 277	0	-1.49114561	1E-15	1.4415419267167138E-15	0
 278	0	-1.43690062	1E-15	1.4415419267167138E-15	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.43690062	1E-15	1.4415419267167138E-15	0
 293	1	0.9331081	1	0	1
 296	0	0.221757889	0.8666667	2.9068906815998465	1
-297	0				
+297	0				0
 299	1	1.13769388	1	0	1
 300	1	1.24829745	1	0	1
 301	0	-1.43690062	1E-15	1.4415419267167138E-15	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.7455783	0.9151356	0.12794252993534275	1
 317	1	1.81665158	1	0	1
 319	0	0.285441637	0.8666667	2.9068906815998465	1
-321	0				
+321	0				0
 323	1	0.8990345	1	0	1
 327	0	-1.49114561	1E-15	1.4415419267167138E-15	0
 328	1	0.8467562	1	0	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	2.95104	1	0	1
 613	0	-1.29436374	1E-15	1.4415419267167138E-15	0
 614	0	-1.4625113	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-1.2706418	1E-15	1.4415419267167138E-15	0
 619	0	-1.19714069	1E-15	1.4415419267167138E-15	0
 621	0	-0.3866408	0.5799383	1.2513268180432666	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.13828516	1E-15	1.4415419267167138E-15	0
 19	0	-0.9969288	1E-15	1.4415419267167138E-15	0
 22	0	-1.259604	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-1.35031986	1E-15	1.4415419267167138E-15	0
 26	0	-1.22985053	1E-15	1.4415419267167138E-15	0
 27	0	-1.11824775	1E-15	1.4415419267167138E-15	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.22317672	1E-15	1.4415419267167138E-15	0
 135	0	-0.8295188	1E-15	1.4415419267167138E-15	0
 136	0	-1.18892586	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-1.3102448	1E-15	1.4415419267167138E-15	0
 142	1	0.6019325	0.875	0.19264507794239591	1
 143	0	-1.00445139	1E-15	1.4415419267167138E-15	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.01599169	1E-15	1.4415419267167138E-15	0
 155	1	0.7134235	0.875	0.19264507794239591	1
 157	0	-1.27964163	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	2.42447567	1	0	1
 160	1	1.81060028	1	0	1
 162	0	-1.20896339	1E-15	1.4415419267167138E-15	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1.72919893	1	0	1
 232	0	-0.038654685	0.6923077	1.7004398041324202	0
 234	0	-0.661043048	1E-15	1.4415419267167138E-15	0
-235	0				
+235	0				0
 236	1	2.13174057	1	0	1
 238	1	2.40485334	1	0	1
 243	0	-0.8018886	1E-15	1.4415419267167138E-15	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	2.9424572	1	0	1
 287	0	-1.22317672	1E-15	1.4415419267167138E-15	0
 289	1	1.71858239	1	0	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	1.42958808	1	0	1
 298	0	-0.7813908	1E-15	1.4415419267167138E-15	0
 302	1	2.925787	1	0	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.35031986	1E-15	1.4415419267167138E-15	0
 310	0	-1.293855	1E-15	1.4415419267167138E-15	0
 313	0	-1.45160127	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 318	0	-1.24103785	1E-15	1.4415419267167138E-15	0
 320	1	1.18153763	1	0	1
 322	0	-1.20896339	1E-15	1.4415419267167138E-15	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-1.40096045	1E-15	1.4415419267167138E-15	0
 408	0	-0.928058	1E-15	1.4415419267167138E-15	0
 410	0	-1.40096045	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	1.731832	1	0	1
 417	0	-1.40096045	1E-15	1.4415419267167138E-15	0
 420	0	-0.7677182	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt
index fed143de3d..0f9cdffb66 100644
--- a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-CV-breast-cancer.nocalibration.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Assigned
 32	1	1.25826859	1
 35	0	-1.41764426	0
 37	0	-0.835641861	0
-40	0		
+40	0		0
 41	1	0.227130175	1
 44	1	1.61423349	1
 45	0	-1.47288513	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Assigned
 138	0	-1.19960022	0
 141	0	-1.47188914	0
 144	0	-1.41764426	0
-145	0		
+145	0		0
 147	0	-1.334388	0
 150	0	-1.48176765	0
 151	1	0.7797704	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Assigned
 154	0	-1.54539037	0
 156	0	-1.35846376	0
 161	0	-1.1599288	0
-164	0		
+164	0		0
 167	1	1.07981849	1
 169	0	-1.5413084	0
 171	0	-1.43690062	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Assigned
 246	1	2.368261	1
 247	1	0.4837153	1
 248	0	-0.934056163	0
-249	0		
+249	0		0
 250	0	-1.41270852	0
 252	0	0.706041336	1
 254	1	1.600352	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Assigned
 269	0	-1.43690062	0
 271	0	-1.1428957	0
 272	1	0.435359716	1
-275	0		
+275	0		0
 276	0	-1.34414315	0
 277	0	-1.49114561	0
 278	0	-1.43690062	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Assigned
 291	0	-1.43690062	0
 293	1	0.9331081	1
 296	0	0.221757889	1
-297	0		
+297	0		0
 299	1	1.13769388	1
 300	1	1.24829745	1
 301	0	-1.43690062	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Assigned
 316	1	0.7455783	1
 317	1	1.81665158	1
 319	0	0.285441637	1
-321	0		
+321	0		0
 323	1	0.8990345	1
 327	0	-1.49114561	0
 328	1	0.8467562	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Assigned
 612	1	2.95104	1
 613	0	-1.29436374	0
 614	0	-1.4625113	0
-617	0		
+617	0		0
 618	0	-1.2706418	0
 619	0	-1.19714069	0
 621	0	-0.3866408	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Assigned
 17	0	-1.13828516	0
 19	0	-0.9969288	0
 22	0	-1.259604	0
-23	1		
+23	1		0
 24	0	-1.35031986	0
 26	0	-1.22985053	0
 27	0	-1.11824775	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Assigned
 134	0	-1.22317672	0
 135	0	-0.8295188	0
 136	0	-1.18892586	0
-139	0		
+139	0		0
 140	0	-1.3102448	0
 142	1	0.6019325	1
 143	0	-1.00445139	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Assigned
 153	0	-1.01599169	0
 155	1	0.7134235	1
 157	0	-1.27964163	0
-158	0		
+158	0		0
 159	1	2.42447567	1
 160	1	1.81060028	1
 162	0	-1.20896339	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Assigned
 231	1	1.72919893	1
 232	0	-0.038654685	0
 234	0	-0.661043048	0
-235	0		
+235	0		0
 236	1	2.13174057	1
 238	1	2.40485334	1
 243	0	-0.8018886	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Assigned
 286	1	2.9424572	1
 287	0	-1.22317672	0
 289	1	1.71858239	1
-292	1		
-294	0		
+292	1		0
+294	0		0
 295	1	1.42958808	1
 298	0	-0.7813908	0
 302	1	2.925787	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Assigned
 307	0	-1.35031986	0
 310	0	-1.293855	0
 313	0	-1.45160127	0
-315	0		
+315	0		0
 318	0	-1.24103785	0
 320	1	1.18153763	1
 322	0	-1.20896339	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Assigned
 407	0	-1.40096045	0
 408	0	-0.928058	0
 410	0	-1.40096045	0
-411	0		
+411	0		0
 412	1	1.731832	1
 417	0	-1.40096045	0
 420	0	-0.7677182	0
diff --git a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt
index 9c673bc10a..b3c0e5b1d8 100644
--- a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt
+++ b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.PAVcalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.133441	1	0	1
 21	1	1.46698761	1	0	1
 22	0	-1.29266214	1E-15	1.4415419267167138E-15	0
-23	1				
+23	1				0
 24	0	-1.38898408	1E-15	1.4415419267167138E-15	0
 25	1	0.2072978	0.8125	0.29956028185890782	1
 26	0	-1.27053475	1E-15	1.4415419267167138E-15	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.7899848	1E-15	1.4415419267167138E-15	0
 38	1	1.07285547	0.955555558	0.065588337627980248	1
 39	1	0.444084644	0.826086938	0.27563447429444238	1
-40	0				
+40	0				0
 41	1	0.278235674	0.8125	0.29956028185890782	1
 42	1	1.82501435	1	0	1
 43	1	0.0648527145	0.8125	0.29956028185890782	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.21864986	1E-15	1.4415419267167138E-15	0
 137	0	-1.34436476	1E-15	1.4415419267167138E-15	0
 138	0	-1.15066063	1E-15	1.4415419267167138E-15	0
-139	0				
+139	0				0
 140	0	-1.34436476	1E-15	1.4415419267167138E-15	0
 141	0	-1.418377	1E-15	1.4415419267167138E-15	0
 142	1	0.605928659	0.826086938	0.27563447429444238	1
 143	0	-1.04888356	1E-15	1.4415419267167138E-15	0
 144	0	-1.36667442	1E-15	1.4415419267167138E-15	0
-145	0				
+145	0				0
 146	1	0.263422	0.8125	0.29956028185890782	1
 147	0	-1.28818154	1E-15	1.4415419267167138E-15	0
 148	0	-0.38141644	0.333333343	0.5849625222189877	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.7075844	0.826086938	0.27563447429444238	1
 156	0	-1.30894148	1E-15	1.4415419267167138E-15	0
 157	0	-1.3149718	1E-15	1.4415419267167138E-15	0
-158	0				
+158	0				0
 159	1	2.41813564	1	0	1
 160	1	1.80749393	1	0	1
 161	0	-1.10798192	1E-15	1.4415419267167138E-15	0
 162	0	-1.24095953	1E-15	1.4415419267167138E-15	0
 163	0	-1.14838839	1E-15	1.4415419267167138E-15	0
-164	0				
+164	0				0
 165	0	-0.9971055	1E-15	1.4415419267167138E-15	0
 166	1	1.77878284	1	0	1
 167	1	1.0986836	0.955555558	0.065588337627980248	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.0348134041	0.727272749	1.8744692325712462	0
 233	1	1.102045	1	0	1
 234	0	-0.709003	0.1	0.15200309583369792	0
-235	0				
+235	0				0
 236	1	2.13387632	1	0	1
 237	1	1.230866	1	0	1
 238	1	2.40226221	1	0	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.38478136	1	0	1
 247	1	0.5292797	0.826086938	0.27563447429444238	1
 248	0	-0.8721206	1E-15	1.4415419267167138E-15	0
-249	0				
+249	0				0
 250	0	-1.3606441	1E-15	1.4415419267167138E-15	0
 251	1	1.35184932	1	0	1
 252	0	0.7461872	0.826086938	2.5235618055722013	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.451641083	0.826086938	0.27563447429444238	1
 273	1	-0.184997916	0.727272749	0.45943157564163517	0
 274	0	-1.1819942	1E-15	1.4415419267167138E-15	0
-275	0				
+275	0				0
 276	0	-1.29266214	1E-15	1.4415419267167138E-15	0
 277	0	-1.4406867	1E-15	1.4415419267167138E-15	0
 278	0	-1.38898408	1E-15	1.4415419267167138E-15	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.698751	1	0	1
 290	0	-1.49238932	1E-15	1.4415419267167138E-15	0
 291	0	-1.38898408	1E-15	1.4415419267167138E-15	0
-292	1				
+292	1				0
 293	1	0.9705	0.955555558	0.065588337627980248	1
-294	0				
+294	0				0
 295	1	1.44576406	1	0	1
 296	0	0.264410973	0.8125	2.4150374992788439	1
-297	0				
+297	0				0
 298	0	-0.785661459	1E-15	1.4415419267167138E-15	0
 299	1	1.16638494	1	0	1
 300	1	1.27287531	1	0	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.6419792	0.826086938	0.27563447429444238	1
 313	0	-1.49238932	1E-15	1.4415419267167138E-15	0
 314	0	-1.4823153	1E-15	1.4415419267167138E-15	0
-315	0				
+315	0				0
 316	1	0.773257732	0.826086938	0.27563447429444238	1
 317	1	1.83582067	1	0	1
 318	0	-1.26409817	1E-15	1.4415419267167138E-15	0
 319	0	0.303462982	0.8125	2.4150374992788439	1
 320	1	1.16069293	1	0	1
-321	0				
+321	0				0
 322	0	-1.24095953	1E-15	1.4415419267167138E-15	0
 323	1	0.909108639	0.955555558	0.065588337627980248	1
 324	0	-1.38898408	1E-15	1.4415419267167138E-15	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-0.9617897	1E-15	1.4415419267167138E-15	0
 409	0	-1.22467291	1E-15	1.4415419267167138E-15	0
 410	0	-1.4406867	1E-15	1.4415419267167138E-15	0
-411	0				
+411	0				0
 412	1	1.77363062	1	0	1
 413	0	-1.02494574	1E-15	1.4415419267167138E-15	0
 414	1	1.26032782	1	0	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.408303	1E-15	1.4415419267167138E-15	0
 615	0	-1.0826714	1E-15	1.4415419267167138E-15	0
 616	0	-1.29266214	1E-15	1.4415419267167138E-15	0
-617	0				
+617	0				0
 618	0	-1.21864986	1E-15	1.4415419267167138E-15	0
 619	0	-1.14463758	1E-15	1.4415419267167138E-15	0
 620	0	-1.29266214	1E-15	1.4415419267167138E-15	0
diff --git a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt
index c5e41e5240..c72088d43c 100644
--- a/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt
+++ b/test/BaselineOutput/SingleRelease/LinearSVM/LinearSVM-TrainTest-breast-cancer.nocalibration.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Assigned
 20	1	1.133441	1
 21	1	1.46698761	1
 22	0	-1.29266214	0
-23	1		
+23	1		0
 24	0	-1.38898408	0
 25	1	0.2072978	1
 26	0	-1.27053475	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Assigned
 37	0	-0.7899848	0
 38	1	1.07285547	1
 39	1	0.444084644	1
-40	0		
+40	0		0
 41	1	0.278235674	1
 42	1	1.82501435	1
 43	1	0.0648527145	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Assigned
 136	0	-1.21864986	0
 137	0	-1.34436476	0
 138	0	-1.15066063	0
-139	0		
+139	0		0
 140	0	-1.34436476	0
 141	0	-1.418377	0
 142	1	0.605928659	1
 143	0	-1.04888356	0
 144	0	-1.36667442	0
-145	0		
+145	0		0
 146	1	0.263422	1
 147	0	-1.28818154	0
 148	0	-0.38141644	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Assigned
 155	1	0.7075844	1
 156	0	-1.30894148	0
 157	0	-1.3149718	0
-158	0		
+158	0		0
 159	1	2.41813564	1
 160	1	1.80749393	1
 161	0	-1.10798192	0
 162	0	-1.24095953	0
 163	0	-1.14838839	0
-164	0		
+164	0		0
 165	0	-0.9971055	0
 166	1	1.77878284	1
 167	1	1.0986836	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Assigned
 232	0	-0.0348134041	0
 233	1	1.102045	1
 234	0	-0.709003	0
-235	0		
+235	0		0
 236	1	2.13387632	1
 237	1	1.230866	1
 238	1	2.40226221	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Assigned
 246	1	2.38478136	1
 247	1	0.5292797	1
 248	0	-0.8721206	0
-249	0		
+249	0		0
 250	0	-1.3606441	0
 251	1	1.35184932	1
 252	0	0.7461872	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Assigned
 272	1	0.451641083	1
 273	1	-0.184997916	0
 274	0	-1.1819942	0
-275	0		
+275	0		0
 276	0	-1.29266214	0
 277	0	-1.4406867	0
 278	0	-1.38898408	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Assigned
 289	1	1.698751	1
 290	0	-1.49238932	0
 291	0	-1.38898408	0
-292	1		
+292	1		0
 293	1	0.9705	1
-294	0		
+294	0		0
 295	1	1.44576406	1
 296	0	0.264410973	1
-297	0		
+297	0		0
 298	0	-0.785661459	0
 299	1	1.16638494	1
 300	1	1.27287531	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Assigned
 312	1	0.6419792	1
 313	0	-1.49238932	0
 314	0	-1.4823153	0
-315	0		
+315	0		0
 316	1	0.773257732	1
 317	1	1.83582067	1
 318	0	-1.26409817	0
 319	0	0.303462982	1
 320	1	1.16069293	1
-321	0		
+321	0		0
 322	0	-1.24095953	0
 323	1	0.909108639	1
 324	0	-1.38898408	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Assigned
 408	0	-0.9617897	0
 409	0	-1.22467291	0
 410	0	-1.4406867	0
-411	0		
+411	0		0
 412	1	1.77363062	1
 413	0	-1.02494574	0
 414	1	1.26032782	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Assigned
 614	0	-1.408303	0
 615	0	-1.0826714	0
 616	0	-1.29266214	0
-617	0		
+617	0		0
 618	0	-1.21864986	0
 619	0	-1.14463758	0
 620	0	-1.29266214	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.txt
index 55744d3dbb..05d8592b8a 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	7.01161575	0.999099433	0.0012998283148002473	1
 35	0	-5.546275	0.0038867984	0.0056183906346792553	0
 37	0	-0.627175331	0.3481513	0.61739094617065504	0
-40	0				
+40	0				0
 41	1	3.0365572	0.9541986	0.067638527006529184	1
 44	1	6.61341858	0.998659551	0.0019351561965343684	1
 45	0	-5.565003	0.00381495967	0.0055143486004666058	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.72209072	0.008818108	0.012778263407408707	0
 141	0	-6.18090439	0.002064286	0.0029812133205916491	0
 144	0	-5.546275	0.0038867984	0.0056183906346792553	0
-145	0				
+145	0				0
 147	0	-5.305633	0.0049390397	0.0071431828757896592	0
 150	0	-5.43029261	0.004362697	0.0063078105710409225	0
 151	1	4.990402	0.993243039	0.0097813179599174817	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.58201027	0.00138314639	0.0019968397134892645	0
 156	0	-5.6663394	0.00344857574	0.0049838416366178697	0
 161	0	-3.992939	0.0181113519	0.026368671070599831	0
-164	0				
+164	0				0
 167	1	6.79999542	0.9988875	0.0016059215653949079	1
 169	0	-6.41288567	0.00163759827	0.0023644914709276374	0
 171	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	10.4554977	0.9999712	4.1534408054175585E-05	1
 247	1	2.7647686	0.940742	0.088128954823708028	1
 248	0	-3.52696	0.0285547972	0.041795476162409473	0
-249	0				
+249	0				0
 250	0	-6.30096865	0.00183116761	0.0026442381917314273	0
 252	0	4.46767044	0.988656163	6.4619475094968903	1
 254	1	5.268241	0.994873762	0.007414618780919654	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.312752	0.004904177	0.007092637921430613	0
 271	0	-3.70832729	0.02393173	0.034946036680259647	0
 272	1	3.75608158	0.9771588	0.033335080773514915	1
-275	0				
+275	0				0
 276	0	-5.145169	0.005793728	0.0083828901690503332	0
 277	0	-5.947381	0.002605866	0.0037643767357215252	0
 278	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.312752	0.004904177	0.007092637921430613	0
 293	1	4.889887	0.992533863	0.0108117709104356	1
 296	0	1.11456966	0.752980053	2.0173005524167049	1
-297	0				
+297	0				0
 299	1	7.92421341	0.999638259	0.00052197576964742038	1
 300	1	5.01128674	0.993381739	0.009579868932513079	1
 301	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.64061546	0.974434555	0.037362801100438832	1
 317	1	8.889477	0.9998622	0.00019882564438936136	1
 319	0	2.932189	0.9494149	4.3051439460642333	1
-321	0				
+321	0				0
 323	1	5.11123276	0.994007468	0.0086714037349760222	1
 327	0	-5.947381	0.002605866	0.0037643767357215252	0
 328	1	3.24846554	0.962617934	0.054964793658751787	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	16.72465	0.99999994	8.5991327994145617E-08	1
 613	0	-5.02813625	0.00650837226	0.0094202851039732072	0
 614	0	-5.6638155	0.00345726055	0.0049964145907412149	0
-617	0				
+617	0				0
 618	0	-4.744063	0.008628122	0.012501759455550775	0
 619	0	-4.34295654	0.01283126	0.01863138517568386	0
 621	0	0.373829842	0.5923841	1.2947177664921086	1
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.23449326	0.0142802689	0.020750590335179415	0
 19	0	-3.10273981	0.04299438	0.063400697943788428	0
 22	0	-5.130806	0.00587705	0.0085038042327941973	0
-23	1				
+23	1				0
 24	0	-5.932124	0.002645822	0.0038221729188529165	0
 26	0	-5.0699935	0.006243238	0.0090353231046563232	0
 27	0	-3.99905157	0.01800297	0.026209433910245255	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.12534046	0.00590906851	0.0085502708566916	0
 135	0	-2.97098112	0.0487542	0.072109916649189282	0
 136	0	-4.56492853	0.0103033585	0.014941712057931327	0
-139	0				
+139	0				0
 140	0	-5.461241	0.00423030974	0.0061159922992663762	0
 142	1	3.05590534	0.9550368	0.066371741280747978	1
 143	0	-5.35564375	0.004699242	0.0067955523991724961	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.276688	0.0136983329	0.019899122722508662	0
 155	1	1.77740765	0.8553765	0.22536855303918271	1
 157	0	-5.366247	0.004649908	0.0067240441834850199	0
-158	0				
+158	0				0
 159	1	8.96132851	0.999871731	0.0001850652016644095	1
 160	1	6.856139	0.998948157	0.001518287560141836	1
 162	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.663686	0.9965423	0.0049970870434534837	1
 232	0	0.928171158	0.71670413	1.8196185260804569	1
 234	0	-3.391735	0.0325547643	0.047748098148187916	0
-235	0				
+235	0				0
 236	1	7.88262749	0.9996229	0.00054416973071506056	1
 238	1	8.651073	0.9998251	0.00025232061237670696	1
 243	0	-4.03390265	0.0173970815	0.025319570708974903	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.9212322	0.99998194	2.6055606891255495E-05	1
 287	0	-5.12534046	0.00590906851	0.0085502708566916	0
 289	1	5.185871	0.9944361	0.0080494462952667781	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77450371	0.9916284	0.012128492162908918	1
 298	0	-2.54918242	0.07248143	0.10855193009256793	0
 302	1	11.1919193	0.999986231	1.9864132926342996E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.932124	0.002645822	0.0038221729188529165	0
 310	0	-5.691217	0.00336412713	0.0048615916252809817	0
 313	0	-6.59299469	0.0013680571	0.0019750404849533288	0
-315	0				
+315	0				0
 318	0	-5.91572762	0.00268944423	0.0038852748092412133	0
 320	1	4.1229	0.9840607	0.023180779648038535	1
 322	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 408	0	-4.386099	0.0122961234	0.017849522550602435	0
 410	0	-6.26255941	0.00190273311	0.0027476785076986981	0
-411	0				
+411	0				0
 412	1	7.037607	0.99912256	0.0012664339928697493	1
 417	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 420	0	-3.338777	0.0342646	0.050300135586962377	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt
index 0a4ce514a2..44c3149a1c 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-CV-breast-cancer.withThreshold.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	7.01161575	0.999099433	0.0012998283148002473	1
 35	0	-5.546275	0.0038867984	0.0056183906346792553	0
 37	0	-0.627175331	0.3481513	0.61739094617065504	0
-40	0				
+40	0				0
 41	1	3.0365572	0.9541986	0.067638527006529184	1
 44	1	6.61341858	0.998659551	0.0019351561965343684	1
 45	0	-5.565003	0.00381495967	0.0055143486004666058	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.72209072	0.008818108	0.012778263407408707	0
 141	0	-6.18090439	0.002064286	0.0029812133205916491	0
 144	0	-5.546275	0.0038867984	0.0056183906346792553	0
-145	0				
+145	0				0
 147	0	-5.305633	0.0049390397	0.0071431828757896592	0
 150	0	-5.43029261	0.004362697	0.0063078105710409225	0
 151	1	4.990402	0.993243039	0.0097813179599174817	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.58201027	0.00138314639	0.0019968397134892645	0
 156	0	-5.6663394	0.00344857574	0.0049838416366178697	0
 161	0	-3.992939	0.0181113519	0.026368671070599831	0
-164	0				
+164	0				0
 167	1	6.79999542	0.9988875	0.0016059215653949079	1
 169	0	-6.41288567	0.00163759827	0.0023644914709276374	0
 171	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	10.4554977	0.9999712	4.1534408054175585E-05	1
 247	1	2.7647686	0.940742	0.088128954823708028	0
 248	0	-3.52696	0.0285547972	0.041795476162409473	0
-249	0				
+249	0				0
 250	0	-6.30096865	0.00183116761	0.0026442381917314273	0
 252	0	4.46767044	0.988656163	6.4619475094968903	1
 254	1	5.268241	0.994873762	0.007414618780919654	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.312752	0.004904177	0.007092637921430613	0
 271	0	-3.70832729	0.02393173	0.034946036680259647	0
 272	1	3.75608158	0.9771588	0.033335080773514915	1
-275	0				
+275	0				0
 276	0	-5.145169	0.005793728	0.0083828901690503332	0
 277	0	-5.947381	0.002605866	0.0037643767357215252	0
 278	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.312752	0.004904177	0.007092637921430613	0
 293	1	4.889887	0.992533863	0.0108117709104356	1
 296	0	1.11456966	0.752980053	2.0173005524167049	0
-297	0				
+297	0				0
 299	1	7.92421341	0.999638259	0.00052197576964742038	1
 300	1	5.01128674	0.993381739	0.009579868932513079	1
 301	0	-5.312752	0.004904177	0.007092637921430613	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.64061546	0.974434555	0.037362801100438832	1
 317	1	8.889477	0.9998622	0.00019882564438936136	1
 319	0	2.932189	0.9494149	4.3051439460642333	0
-321	0				
+321	0				0
 323	1	5.11123276	0.994007468	0.0086714037349760222	1
 327	0	-5.947381	0.002605866	0.0037643767357215252	0
 328	1	3.24846554	0.962617934	0.054964793658751787	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	16.72465	0.99999994	8.5991327994145617E-08	1
 613	0	-5.02813625	0.00650837226	0.0094202851039732072	0
 614	0	-5.6638155	0.00345726055	0.0049964145907412149	0
-617	0				
+617	0				0
 618	0	-4.744063	0.008628122	0.012501759455550775	0
 619	0	-4.34295654	0.01283126	0.01863138517568386	0
 621	0	0.373829842	0.5923841	1.2947177664921086	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.23449326	0.0142802689	0.020750590335179415	0
 19	0	-3.10273981	0.04299438	0.063400697943788428	0
 22	0	-5.130806	0.00587705	0.0085038042327941973	0
-23	1				
+23	1				0
 24	0	-5.932124	0.002645822	0.0038221729188529165	0
 26	0	-5.0699935	0.006243238	0.0090353231046563232	0
 27	0	-3.99905157	0.01800297	0.026209433910245255	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.12534046	0.00590906851	0.0085502708566916	0
 135	0	-2.97098112	0.0487542	0.072109916649189282	0
 136	0	-4.56492853	0.0103033585	0.014941712057931327	0
-139	0				
+139	0				0
 140	0	-5.461241	0.00423030974	0.0061159922992663762	0
 142	1	3.05590534	0.9550368	0.066371741280747978	1
 143	0	-5.35564375	0.004699242	0.0067955523991724961	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.276688	0.0136983329	0.019899122722508662	0
 155	1	1.77740765	0.8553765	0.22536855303918271	0
 157	0	-5.366247	0.004649908	0.0067240441834850199	0
-158	0				
+158	0				0
 159	1	8.96132851	0.999871731	0.0001850652016644095	1
 160	1	6.856139	0.998948157	0.001518287560141836	1
 162	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.663686	0.9965423	0.0049970870434534837	1
 232	0	0.928171158	0.71670413	1.8196185260804569	0
 234	0	-3.391735	0.0325547643	0.047748098148187916	0
-235	0				
+235	0				0
 236	1	7.88262749	0.9996229	0.00054416973071506056	1
 238	1	8.651073	0.9998251	0.00025232061237670696	1
 243	0	-4.03390265	0.0173970815	0.025319570708974903	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.9212322	0.99998194	2.6055606891255495E-05	1
 287	0	-5.12534046	0.00590906851	0.0085502708566916	0
 289	1	5.185871	0.9944361	0.0080494462952667781	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.77450371	0.9916284	0.012128492162908918	1
 298	0	-2.54918242	0.07248143	0.10855193009256793	0
 302	1	11.1919193	0.999986231	1.9864132926342996E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.932124	0.002645822	0.0038221729188529165	0
 310	0	-5.691217	0.00336412713	0.0048615916252809817	0
 313	0	-6.59299469	0.0013680571	0.0019750404849533288	0
-315	0				
+315	0				0
 318	0	-5.91572762	0.00268944423	0.0038852748092412133	0
 320	1	4.1229	0.9840607	0.023180779648038535	1
 322	0	-4.80037	0.008159574	0.011820066323398703	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 408	0	-4.386099	0.0122961234	0.017849522550602435	0
 410	0	-6.26255941	0.00190273311	0.0027476785076986981	0
-411	0				
+411	0				0
 412	1	7.037607	0.99912256	0.0012664339928697493	1
 417	0	-6.26255941	0.00190273311	0.0027476785076986981	0
 420	0	-3.338777	0.0342646	0.050300135586962377	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt
index 2748bad72f..b1d74e635f 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	5.917115	0.9973143	0.003879895635620469	1
 35	0	-5.023262	0.006539965	0.0094661631818091386	0
 37	0	-1.38112783	0.200827926	0.3234219246434899	0
-40	0				
+40	0				0
 41	1	1.99977684	0.880773664	0.18315676412764836	1
 44	1	6.1460495	0.997862637	0.0030868629883528767	1
 45	0	-4.92853165	0.00718512246	0.010403360173725132	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.17745543	0.0151058007	0.021959341229968121	0
 141	0	-5.50801945	0.00403775927	0.0058370475132605874	0
 144	0	-5.023262	0.006539965	0.0094661631818091386	0
-145	0				
+145	0				0
 147	0	-4.81479263	0.00804367848	0.011651498579728541	0
 150	0	-4.92451668	0.00721382024	0.01044506254471955	0
 151	1	4.048602	0.9828524	0.024953319944645107	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-5.80309772	0.00300910859	0.0043477707884351756	0
 156	0	-4.933721	0.00714819832	0.010349705365439381	0
 161	0	-3.81854677	0.0214878246	0.031338292831631254	0
-164	0				
+164	0				0
 167	1	7.07203674	0.999152243	0.0012235733412714462	1
 169	0	-5.652446	0.00349665456	0.0050534464360921993	0
 171	0	-4.83358335	0.007895125	0.011435459622816726	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.218597	0.9999008	0.00014309666195095306	1
 247	1	1.9463377	0.87504673	0.19256803177214576	1
 248	0	-3.2993412	0.0355937965	0.052287163877458576	0
-249	0				
+249	0				0
 250	0	-5.418478	0.004414317	0.006382611353481173	0
 252	0	3.48067	0.970132768	5.0652926577610451	1
 254	1	4.863985	0.9923395	0.011094325676462969	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-4.83358335	0.007895125	0.011435459622816726	0
 271	0	-3.65327024	0.0252520833	0.036898928715096181	0
 272	1	3.02218533	0.9535664	0.068594734962942897	1
-275	0				
+275	0				0
 276	0	-4.72818375	0.008765012	0.012700983189760973	0
 277	0	-5.3183403	0.00487697963	0.00705320751084503	0
 278	0	-4.83358335	0.007895125	0.011435459622816726	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-4.83358335	0.007895125	0.011435459622816726	0
 293	1	3.6722765	0.975211561	0.036212866280089365	1
 296	0	0.9506779	0.7212515	1.8429639897619017	1
-297	0				
+297	0				0
 299	1	5.993658	0.9975117	0.0035943536619517991	1
 300	1	5.41301346	0.9955616	0.0064175103553020287	1
 301	0	-4.83358335	0.007895125	0.011435459622816726	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	2.857479	0.945704	0.080539421519246923	1
 317	1	7.483817	0.9994382	0.00081069597738820146	1
 319	0	2.14308548	0.895020843	3.2518251711052208	1
-321	0				
+321	0				0
 323	1	4.38443756	0.987683654	0.017879061305842645	1
 327	0	-5.3183403	0.00487697963	0.00705320751084503	0
 328	1	1.9153614	0.8716203	0.19822830198625993	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	15.0148582	0.9999997	4.2995669122556443E-07	1
 613	0	-4.76532364	0.008448151	0.012239880753341762	0
 614	0	-5.114196	0.005974896	0.00864580721752186	0
-617	0				
+617	0				0
 618	0	-4.43310547	0.0117381271	0.017034712310540854	0
 619	0	-4.138027	0.0157037526	0.022835500585175472	0
 621	0	-0.147964478	0.463076234	0.89721082981393785	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.094967	0.0163834114	0.023832028779250634	0
 19	0	-3.158533	0.0407563634	0.06003080556474015	0
 22	0	-4.786547	0.008272208	0.011983909171361835	0
-23	1				
+23	1				0
 24	0	-5.49961758	0.00407168828	0.0058861960152521283	0
 26	0	-4.637971	0.009584561	0.013894290826829943	0
 27	0	-3.85011339	0.02083403	0.030374676365783088	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-4.786547	0.008272208	0.011983909171361835	0
 135	0	-2.91646814	0.0513454638	0.07604528657651706	0
 136	0	-4.31833	0.01314697	0.019092852440504127	0
-139	0				
+139	0				0
 140	0	-5.00991058	0.006627286	0.009592975357514695	0
 142	1	2.566639	0.9286834	0.10674124733849408	1
 143	0	-4.68576	0.009141385	0.013248879501449318	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-3.91140127	0.0196197983	0.028586744893093978	0
 155	1	1.73489761	0.8500378	0.23440107518588552	1
 157	0	-5.03140068	0.00648729829	0.0093896829482070059	0
-158	0				
+158	0				0
 159	1	8.209714	0.9997281	0.00039234577165867646	1
 160	1	6.214038	0.9980028	0.0028841924162386562	1
 162	0	-4.563184	0.0103211654	0.014967669647872791	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.128908	0.994111836	0.0085199331359509835	1
 232	0	0.387944221	0.5957877	1.3068148861794051	1
 234	0	-3.05071926	0.04518643	0.066709024779774861	0
-235	0				
+235	0				0
 236	1	7.45407867	0.999421239	0.00083521748895634131	1
 238	1	8.351737	0.9997641	0.00034039381967173406	1
 243	0	-3.79230738	0.02204652	0.032162254419967784	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.2351351	0.9999641	5.1767706679585828E-05	1
 287	0	-4.786547	0.008272208	0.011983909171361835	0
 289	1	5.007719	0.993358254	0.0096139756423385195	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.08445454	0.9834463	0.024081816959951673	1
 298	0	-2.520249	0.07445079	0.11161839829444895	0
 302	1	10.2925406	0.999966145	4.8843899665517181E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.49961758	0.00407168828	0.0058861960152521283	0
 310	0	-5.254764	0.00519544445	0.0075149807235167431	0
 313	0	-5.94634438	0.00260856142	0.0037682756571934027	0
-315	0				
+315	0				0
 318	0	-5.49961758	0.00407168828	0.0058861960152521283	0
 320	1	3.84560966	0.9790739	0.030510363432469476	1
 322	0	-4.563184	0.0103211654	0.014967669647872791	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-5.722981	0.003259291	0.00470984242704696	0
 408	0	-3.98740244	0.0182100739	0.026513731287650329	0
 410	0	-5.722981	0.003259291	0.00470984242704696	0
-411	0				
+411	0				0
 412	1	5.972435	0.997458458	0.0036713375244963246	1
 417	0	-5.722981	0.003259291	0.00470984242704696	0
 420	0	-3.14838743	0.0411548652	0.060630273661156198	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt
index c81880f594..aad01de654 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-GaussianNorm-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	5.678712	0.9965937	0.0049226209615764287	1
 21	1	6.001464	0.997531	0.0035664232425213858	1
 22	0	-5.02218437	0.00654697046	0.009476336418019371	0
-23	1				
+23	1				0
 24	0	-5.557753	0.00384261133	0.0055543948499928858	0
 25	1	0.7356682	0.676047862	0.56480270753052697	1
 26	0	-5.01491547	0.006594418	0.0095452416271748757	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.86437464	0.134193972	0.20788424941725006	0
 38	1	4.26738262	0.986175358	0.020083890425044392	1
 39	1	0.948868752	0.7208876	0.47215375855428471	1
-40	0				
+40	0				0
 41	1	2.21941185	0.9019792	0.14883391736209772	1
 42	1	6.171118	0.997915447	0.00301051350343931	1
 43	1	-0.406847954	0.399668157	1.3231254618912542	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.573848	0.0102128033	0.014809714349895977	0
 137	0	-5.38329029	0.00457168929	0.0066106759896893642	0
 138	0	-4.32377768	0.0130764758	0.018989799023276886	0
-139	0				
+139	0				0
 140	0	-5.38329029	0.00457168929	0.0066106759896893642	0
 141	0	-5.83162737	0.00292472052	0.0042256622529479159	0
 142	1	3.1618576	0.9593734	0.059835633747694031	1
 143	0	-4.83655453	0.007871887	0.011401667353256314	0
 144	0	-5.470522	0.004191393	0.00605960993587892	0
-145	0				
+145	0				0
 146	1	0.0557060242	0.5139229	0.96037607240274647	1
 147	0	-5.47995234	0.00415221555	0.0060028519951750492	0
 148	0	-1.59599066	0.168542728	0.26628596824729922	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.20912266	0.901065767	0.15029568586304221	1
 156	0	-5.58346558	0.003745433	0.0054136621278108544	0
 157	0	-5.109416	0.006003351	0.0086871066895572498	0
-158	0				
+158	0				0
 159	1	9.879018	0.99994874	7.3954435339176224E-05	1
 160	1	6.966673	0.9990581	0.0013594752512588889	1
 161	0	-4.01959	0.0176434461	0.025681337989317106	0
 162	0	-4.661079	0.009367671	0.01357839101244592	0
 163	0	-3.39304066	0.03251367	0.04768681882905737	0
-164	0				
+164	0				0
 165	0	-3.65873766	0.0251178537	0.036700273114887771	0
 166	1	6.106388	0.9977764	0.0032115643460085509	1
 167	1	6.96164227	0.999053359	0.0013663610592643267	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.434880257	0.607038438	1.3475398955993996	1
 233	1	4.62145329	0.9902574	0.014124543390739288	1
 234	0	-3.19655	0.0392957628	0.057835744186683809	0
-235	0				
+235	0				0
 236	1	9.488486	0.9999243	0.00010921311695177715	1
 237	1	5.185233	0.994432569	0.0080545481788837064	1
 238	1	10.3383093	0.999967635	4.6694045347237877E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.706185	0.9998345	0.00023881767606976273	1
 247	1	1.85991	0.865286469	0.20875025156266316	1
 248	0	-3.24698353	0.03743543	0.055044774760243595	0
-249	0				
+249	0				0
 250	0	-5.9445715	0.00261317822	0.0037749537255417041	0
 251	1	6.851535	0.998943269	0.001525346290754842	1
 252	0	3.15871048	0.959250569	4.6170762873605469	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.54124355	0.8236454	0.27990471757503477	1
 273	1	-0.485281944	0.381005645	1.3921157227274092	0
 274	0	-4.467927	0.0113409776	0.016455057773140165	0
-275	0				
+275	0				0
 276	0	-5.02218437	0.00654697046	0.009476336418019371	0
 277	0	-5.918859	0.00268105837	0.0038731439944547637	0
 278	0	-5.557753	0.00384261133	0.0055543948499928858	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	6.391654	0.9983273	0.0024151950596217639	1
 290	0	-6.27996445	0.00186996383	0.0027003130775063206	0
 291	0	-5.557753	0.00384261133	0.0055543948499928858	0
-292	1				
+292	1				0
 293	1	4.062559	0.98308605	0.024610393646554929	1
-294	0				
+294	0				0
 295	1	5.48979473	0.9958883	0.0059441683338054239	1
 296	0	0.7984762	0.689648449	1.6880247409542737	1
-297	0				
+297	0				0
 298	0	-2.82211971	0.05614051	0.083355987427050499	0
 299	1	5.92269325	0.9973292	0.0038583400725341575	1
 300	1	5.553643	0.9961416	0.0055772429838620297	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.505681	0.924539149	0.11319368429557292	1
 313	0	-6.27996445	0.00186996383	0.0027003130775063206	0
 314	0	-5.996913	0.00248024915	0.0035826879721537609	0
-315	0				
+315	0				0
 316	1	2.06765842	0.8877198	0.17182370265537225	1
 317	1	6.799261	0.998886645	0.0016071267852858751	1
 318	0	-5.323591	0.004851562	0.0070163583406618974	0
 319	0	1.16352749	0.7619731	2.0708033667370818	1
 320	1	5.47767448	0.995838344	0.006016528395062894	1
-321	0				
+321	0				0
 322	0	-4.661079	0.009367671	0.01357839101244592	0
 323	1	3.7019043	0.975917757	0.035168522105486828	1
 324	0	-5.557753	0.00384261133	0.0055543948499928858	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.06660128	0.0168468487	0.024511924018010906	0
 409	0	-4.77211475	0.008391453	0.012157388278315496	0
 410	0	-5.918859	0.00268105837	0.0038731439944547637	0
-411	0				
+411	0				0
 412	1	6.93106556	0.999024	0.0014087955764285343	1
 413	0	-3.5143342	0.02890712	0.042318806680098388	0
 414	1	4.808298	0.9919043	0.0117271336749766	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-5.548576	0.00387790077	0.0056055040477979955	0
 615	0	-4.073707	0.0167295579	0.024339819893712551	0
 616	0	-5.02218437	0.00654697046	0.009476336418019371	0
-617	0				
+617	0				0
 618	0	-4.573848	0.0102128033	0.014809714349895977	0
 619	0	-4.12551069	0.0158983991	0.023120824431946189	0
 620	0	-5.02218437	0.00654697046	0.009476336418019371	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt
index 4789a49c72..a31588d1b9 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	7.041827	0.999126256	0.0012610978584151201	1
 21	1	7.16006565	0.9992236	0.0011205580676841706	1
 22	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-23	1				
+23	1				0
 24	0	-6.16573143	0.00209578	0.003026744365055557	0
 25	1	1.140585	0.757787049	0.4001356116356401	1
 26	0	-5.39192247	0.00453257374	0.006553986122637143	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.74917936	0.148150727	0.23132991391158644	0
 38	1	5.25044537	0.9947822	0.0075473881419006704	1
 39	1	1.14784718	0.7591175	0.39760491464649406	1
-40	0				
+40	0				0
 41	1	2.83779049	0.9446841	0.082096136496848479	1
 42	1	5.84602737	0.997117	0.0041653216557672994	1
 43	1	-0.115566254	0.471140563	1.0857705467412089	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.81180668	0.008067538	0.011686200181083801	0
 137	0	-5.771742	0.003104659	0.0044860436134326774	0
 138	0	-4.708121	0.008941052	0.01295722303877558	0
-139	0				
+139	0				0
 140	0	-5.771742	0.003104659	0.0044860436134326774	0
 141	0	-6.35020638	0.00174334215	0.0025173059685722476	0
 142	1	3.59143162	0.9731803	0.039220987499558525	1
 143	0	-5.32383156	0.00485040154	0.0070146760362167319	0
 144	0	-5.96873665	0.00255094632	0.0036849396417204128	0
-145	0				
+145	0				0
 146	1	-0.228344917	0.443160534	1.1740986883981319	0
 147	0	-6.02899933	0.00240211817	0.0034696929544304877	0
 148	0	-1.17236042	0.236428589	0.38916500660996345	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.561039	0.928311646	0.10731887720885433	1
 156	0	-6.32817459	0.0017821081	0.0025733321754180501	0
 157	0	-5.587267	0.00373127544	0.0053931605303660906	0
-158	0				
+158	0				0
 159	1	9.957122	0.9999526	6.836472348564471E-05	1
 160	1	7.81574535	0.999596834	0.00058176260649806227	1
 161	0	-4.194911	0.0148482891	0.02158218175164682	0
 162	0	-5.008802	0.00663458835	0.0096035809636014526	0
 163	0	-4.450941	0.0115330191	0.016735320470494343	0
-164	0				
+164	0				0
 165	0	-3.79370117	0.022016488	0.0321179521831969	0
 166	1	6.78795338	0.998874	0.0016253773809814112	1
 167	1	6.650817	0.9987087	0.0018641198790525675	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.440856934	0.6084632	1.3527802863415537	1
 233	1	5.59169	0.996285141	0.0053693888063565016	1
 234	0	-3.380312	0.0329164639	0.048287580681296273	0
-235	0				
+235	0				0
 236	1	9.42349148	0.9999192	0.00011660894974341421	1
 237	1	5.527053	0.9960381	0.005727196256675989	1
 238	1	10.3295126	0.999967337	4.7124015954602722E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.522981	0.999926865	0.00010551521477366078	1
 247	1	2.22113419	0.9021314	0.14859054441592434	1
 248	0	-3.25320721	0.037211813	0.0547096542674552	0
-249	0				
+249	0				0
 250	0	-6.70964432	0.00121761323	0.0017577148937104486	0
 251	1	8.275113	0.9997453	0.00036748773339945429	1
 252	0	3.75820923	0.97720623	5.4552166396980901	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.25216866	0.777675033	0.36276067331990891	1
 273	1	-0.4770708	0.382944047	1.3847944817499098	0
 274	0	-4.773376	0.008380964	0.01214212852075712	0
-275	0				
+275	0				0
 276	0	-5.39027166	0.00454002852	0.0065647900946516503	0
 277	0	-6.547201	0.00143207016	0.0020675212884715419	0
 278	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	7.07017231	0.999150634	0.0012258970788924348	1
 290	0	-6.928671	0.0009783435	0.0014121422633917285	0
 291	0	-6.16573143	0.00209578	0.003026744365055557	0
-292	1				
+292	1				0
 293	1	5.206727	0.9945503	0.0078837745923848179	1
-294	0				
+294	0				0
 295	1	6.0751133	0.9977059	0.0033135223937081622	1
 296	0	1.04628563	0.740061	1.9437549070362801	1
-297	0				
+297	0				0
 298	0	-2.41310167	0.08217907	0.12371538777024385	0
 299	1	7.396323	0.999386847	0.00088486407096525718	1
 300	1	5.69218445	0.996639132	0.0048568731086720204	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	3.90498447	0.9802564	0.02876897031816629	1
 313	0	-6.928671	0.0009783435	0.0014121422633917285	0
 314	0	-6.664193	0.00127416	0.0018393963949252371	0
-315	0				
+315	0				0
 316	1	2.20020485	0.9002679	0.15157371666802275	1
 317	1	7.75578	0.9995719	0.00061772192605728435	1
 318	0	-5.81475639	0.002974334	0.0042974510254079716	0
 319	0	1.38163567	0.7992536	2.3165538563686012	1
 320	1	5.837037	0.997091	0.0042029227668842466	1
-321	0				
+321	0				0
 322	0	-5.008802	0.00663458835	0.0096035809636014526	0
 323	1	4.26100159	0.9860881	0.020211552173447847	1
 324	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.4899044	0.0110971872	0.016099351806882618	0
 409	0	-5.286586	0.00503353868	0.0072801992795113032	0
 410	0	-6.547201	0.00143207016	0.0020675212884715419	0
-411	0				
+411	0				0
 412	1	7.575248	0.9994873	0.00073988707471124668	1
 413	0	-3.748186	0.0230181254	0.033596298028071243	0
 414	1	5.274519	0.994905651	0.0073683771133106393	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.085728	0.00226994278	0.0032785576690230068	0
 615	0	-4.604435	0.0099082	0.01436579907268937	0
 616	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-617	0				
+617	0				0
 618	0	-4.81180668	0.008067538	0.011686200181083801	0
 619	0	-4.233342	0.0142964814	0.020774319020048612	0
 620	0	-5.39027166	0.00454002852	0.0065647900946516503	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt
index 92afd941f0..105627b7fb 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-TrainTest-breast-cancer.withThreshold.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	7.041827	0.999126256	0.0012610978584151201	1
 21	1	7.16006565	0.9992236	0.0011205580676841706	1
 22	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-23	1				
+23	1				0
 24	0	-6.16573143	0.00209578	0.003026744365055557	0
 25	1	1.140585	0.757787049	0.4001356116356401	0
 26	0	-5.39192247	0.00453257374	0.006553986122637143	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.74917936	0.148150727	0.23132991391158644	0
 38	1	5.25044537	0.9947822	0.0075473881419006704	1
 39	1	1.14784718	0.7591175	0.39760491464649406	0
-40	0				
+40	0				0
 41	1	2.83779049	0.9446841	0.082096136496848479	0
 42	1	5.84602737	0.997117	0.0041653216557672994	1
 43	1	-0.115566254	0.471140563	1.0857705467412089	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.81180668	0.008067538	0.011686200181083801	0
 137	0	-5.771742	0.003104659	0.0044860436134326774	0
 138	0	-4.708121	0.008941052	0.01295722303877558	0
-139	0				
+139	0				0
 140	0	-5.771742	0.003104659	0.0044860436134326774	0
 141	0	-6.35020638	0.00174334215	0.0025173059685722476	0
 142	1	3.59143162	0.9731803	0.039220987499558525	1
 143	0	-5.32383156	0.00485040154	0.0070146760362167319	0
 144	0	-5.96873665	0.00255094632	0.0036849396417204128	0
-145	0				
+145	0				0
 146	1	-0.228344917	0.443160534	1.1740986883981319	0
 147	0	-6.02899933	0.00240211817	0.0034696929544304877	0
 148	0	-1.17236042	0.236428589	0.38916500660996345	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.561039	0.928311646	0.10731887720885433	0
 156	0	-6.32817459	0.0017821081	0.0025733321754180501	0
 157	0	-5.587267	0.00373127544	0.0053931605303660906	0
-158	0				
+158	0				0
 159	1	9.957122	0.9999526	6.836472348564471E-05	1
 160	1	7.81574535	0.999596834	0.00058176260649806227	1
 161	0	-4.194911	0.0148482891	0.02158218175164682	0
 162	0	-5.008802	0.00663458835	0.0096035809636014526	0
 163	0	-4.450941	0.0115330191	0.016735320470494343	0
-164	0				
+164	0				0
 165	0	-3.79370117	0.022016488	0.0321179521831969	0
 166	1	6.78795338	0.998874	0.0016253773809814112	1
 167	1	6.650817	0.9987087	0.0018641198790525675	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.440856934	0.6084632	1.3527802863415537	0
 233	1	5.59169	0.996285141	0.0053693888063565016	1
 234	0	-3.380312	0.0329164639	0.048287580681296273	0
-235	0				
+235	0				0
 236	1	9.42349148	0.9999192	0.00011660894974341421	1
 237	1	5.527053	0.9960381	0.005727196256675989	1
 238	1	10.3295126	0.999967337	4.7124015954602722E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.522981	0.999926865	0.00010551521477366078	1
 247	1	2.22113419	0.9021314	0.14859054441592434	0
 248	0	-3.25320721	0.037211813	0.0547096542674552	0
-249	0				
+249	0				0
 250	0	-6.70964432	0.00121761323	0.0017577148937104486	0
 251	1	8.275113	0.9997453	0.00036748773339945429	1
 252	0	3.75820923	0.97720623	5.4552166396980901	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.25216866	0.777675033	0.36276067331990891	0
 273	1	-0.4770708	0.382944047	1.3847944817499098	0
 274	0	-4.773376	0.008380964	0.01214212852075712	0
-275	0				
+275	0				0
 276	0	-5.39027166	0.00454002852	0.0065647900946516503	0
 277	0	-6.547201	0.00143207016	0.0020675212884715419	0
 278	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	7.07017231	0.999150634	0.0012258970788924348	1
 290	0	-6.928671	0.0009783435	0.0014121422633917285	0
 291	0	-6.16573143	0.00209578	0.003026744365055557	0
-292	1				
+292	1				0
 293	1	5.206727	0.9945503	0.0078837745923848179	1
-294	0				
+294	0				0
 295	1	6.0751133	0.9977059	0.0033135223937081622	1
 296	0	1.04628563	0.740061	1.9437549070362801	0
-297	0				
+297	0				0
 298	0	-2.41310167	0.08217907	0.12371538777024385	0
 299	1	7.396323	0.999386847	0.00088486407096525718	1
 300	1	5.69218445	0.996639132	0.0048568731086720204	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	3.90498447	0.9802564	0.02876897031816629	1
 313	0	-6.928671	0.0009783435	0.0014121422633917285	0
 314	0	-6.664193	0.00127416	0.0018393963949252371	0
-315	0				
+315	0				0
 316	1	2.20020485	0.9002679	0.15157371666802275	0
 317	1	7.75578	0.9995719	0.00061772192605728435	1
 318	0	-5.81475639	0.002974334	0.0042974510254079716	0
 319	0	1.38163567	0.7992536	2.3165538563686012	0
 320	1	5.837037	0.997091	0.0042029227668842466	1
-321	0				
+321	0				0
 322	0	-5.008802	0.00663458835	0.0096035809636014526	0
 323	1	4.26100159	0.9860881	0.020211552173447847	1
 324	0	-6.16573143	0.00209578	0.003026744365055557	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.4899044	0.0110971872	0.016099351806882618	0
 409	0	-5.286586	0.00503353868	0.0072801992795113032	0
 410	0	-6.547201	0.00143207016	0.0020675212884715419	0
-411	0				
+411	0				0
 412	1	7.575248	0.9994873	0.00073988707471124668	1
 413	0	-3.748186	0.0230181254	0.033596298028071243	0
 414	1	5.274519	0.994905651	0.0073683771133106393	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.085728	0.00226994278	0.0032785576690230068	0
 615	0	-4.604435	0.0099082	0.01436579907268937	0
 616	0	-5.39027166	0.00454002852	0.0065647900946516503	0
-617	0				
+617	0				0
 618	0	-4.81180668	0.008067538	0.011686200181083801	0
 619	0	-4.233342	0.0142964814	0.020774319020048612	0
 620	0	-5.39027166	0.00454002852	0.0065647900946516503	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt
index 946584d7cb..199b9a59b7 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	4.455554	0.98851943	0.016658771299360001	1
 35	0	-5.20966339	0.005433825	0.0078607284616035548	0
 37	0	-1.95550251	0.1239546	0.19092245979854006	0
-40	0				
+40	0				0
 41	1	1.363338	0.796301663	0.32861302447496599	1
 44	1	2.93189621	0.949400842	0.074910765340690438	1
 45	0	-5.4227767	0.00439546537	0.0063552935777515963	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.283581	0.01360552	0.019763368834071083	0
 141	0	-5.903559	0.0027222808	0.0039327765009182425	0
 144	0	-5.20966339	0.005433825	0.0078607284616035548	0
-145	0				
+145	0				0
 147	0	-4.808229	0.008096219	0.011727915268260366	0
 150	0	-4.955528	0.00699508563	0.010127237230146099	0
 151	1	2.9794178	0.9516356	0.071518853245330763	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.343319	0.00175536959	0.0025346883174766728	0
 156	0	-4.870145	0.00761383865	0.011026477645071437	0
 161	0	-3.876839	0.0202957559	0.029581804866342248	0
-164	0				
+164	0				0
 167	1	1.63665962	0.8370799	0.25656278900168672	1
 169	0	-6.067718	0.00231109979	0.0033380709957833601	0
 171	0	-4.955528	0.00699508563	0.010127237230146099	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	6.373105	0.9982961	0.0024603307167519865	1
 247	1	1.08481979	0.747405	0.42003789409759523	1
 248	0	-3.67766953	0.0246584155	0.036020526273661445	0
-249	0				
+249	0				0
 250	0	-5.56404066	0.00381861837	0.0055196472135604522	0
 252	0	2.67256546	0.935388267	3.9520600195019679	1
 254	1	2.64337635	0.933601558	0.099121125939627047	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-4.955528	0.00699508563	0.010127237230146099	0
 271	0	-3.63624859	0.0256744642	0.037524217400354012	0
 272	1	2.26432514	0.905879	0.14260970234578763	1
-275	0				
+275	0				0
 276	0	-5.20966339	0.005433825	0.0078607284616035548	0
 277	0	-5.6494236	0.003507201	0.0050687153327134771	0
 278	0	-4.955528	0.00699508563	0.010127237230146099	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-4.955528	0.00699508563	0.010127237230146099	0
 293	1	2.05892181	0.886846	0.17324448166666195	1
 296	0	1.99554062	0.880328059	3.0628431682446857	1
-297	0				
+297	0				0
 299	1	3.69336033	0.9757162	0.035466552037373179	1
 300	1	4.02837372	0.9825081	0.025458759934045509	1
 301	0	-4.955528	0.00699508563	0.010127237230146099	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	2.94207382	0.9498875	0.074171415588786135	1
 317	1	4.312872	0.986782	0.019196674360521217	1
 319	0	2.41989422	0.9183318	3.6140817927103961	1
-321	0				
+321	0				0
 323	1	3.56970787	0.972607434	0.040070476517068486	1
 327	0	-5.6494236	0.003507201	0.0050687153327134771	0
 328	1	1.70264626	0.845880032	0.24147502978012392	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	7.478863	0.9994354	0.00081473984708772015	1
 613	0	-4.91670847	0.00726995664	0.010526641032229434	0
 614	0	-5.20966339	0.005433825	0.0078607284616035548	0
-617	0				
+617	0				0
 618	0	-4.769904	0.008409867	0.01218417928555986	0
 619	0	-4.330144	0.0129945707	0.018870074173474232	0
 621	0	-0.284356117	0.429386139	0.80941330227154873	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-3.99180722	0.0181314889	0.026398258875503611	0
 19	0	-3.49091744	0.0295717642	0.043306566793261343	0
 22	0	-4.74231339	0.008643099	0.012523555687056959	0
-23	1				
+23	1				0
 24	0	-4.99358654	0.00673562335	0.0097503246472711684	0
 26	0	-4.230923	0.01433061	0.020824270758417435	0
 27	0	-3.74053383	0.0231908429	0.0338513700113664	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-4.74265528	0.00864017	0.012519293184591884	0
 135	0	-2.40284228	0.08295622	0.12493748028384198	0
 136	0	-4.24142361	0.0141830426	0.020608297294341209	0
-139	0				
+139	0				0
 140	0	-4.99192953	0.006746718	0.0097664397610658042	0
 142	1	1.883389	0.8679999	0.20423319963131603	1
 143	0	-3.93245554	0.0192188919	0.027996904861385053	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-3.71085787	0.02387269	0.034858773809671437	0
 155	1	2.1317234	0.8939485	0.1617363815870177	1
 157	0	-4.492697	0.0110665858	0.016054708591916572	0
-158	0				
+158	0				0
 159	1	7.019025	0.9991061	0.0012901886373564615	1
 160	1	5.00210667	0.9933211	0.0096679074407147667	1
 162	0	-4.492697	0.0110665858	0.016054708591916572	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	4.06135273	0.983066	0.02463978413547805	1
 232	0	0.582720757	0.641693234	1.4807328100816015	1
 234	0	-2.76217723	0.0594026	0.08835075047841523	0
-235	0				
+235	0				0
 236	1	5.42756176	0.995625436	0.0063250060270779312	1
 238	1	6.00247669	0.9975335	0.0035628026721853763	1
 243	0	-3.18360639	0.039787326	0.058574116415727635	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	7.122633	0.999194	0.0011632435375058345	1
 287	0	-4.74265528	0.00864017	0.012519293184591884	0
 289	1	5.24414349	0.994749367	0.0075950186704868833	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	3.85042763	0.979172349	0.030365276805999493	1
 298	0	-2.97889614	0.0483884327	0.07155528637722855	0
 302	1	7.28154945	0.999312341	0.00099242318488484949	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-4.99358654	0.00673562335	0.0097503246472711684	0
 310	0	-4.74265528	0.00864017	0.012519293184591884	0
 313	0	-5.49281931	0.004099349	0.005926265742136525	0
-315	0				
+315	0				0
 318	0	-4.994271	0.006731047	0.0097436773674529319	0
 320	1	3.98940563	0.9818257	0.026461150371251282	1
 322	0	-4.492697	0.0110665858	0.016054708591916572	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-5.243203	0.00525554	0.0076021355607147146	0
 408	0	-2.50673819	0.07538716	0.11307869372093513	0
 410	0	-5.243203	0.00525554	0.0076021355607147146	0
-411	0				
+411	0				0
 412	1	4.41673565	0.9880704	0.017314215991460075	1
 417	0	-5.243203	0.00525554	0.0076021355607147146	0
 420	0	-2.416037	0.08195794	0.12336783697816152	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt
index fc9c09274b..e1541ef4c5 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-bin-norm-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	3.60211229	0.973457634	0.038809901663734138	1
 21	1	4.16481066	0.9847049	0.022236640568523543	1
 22	0	-5.531984	0.003942524	0.0056991017626305011	0
-23	1				
+23	1				0
 24	0	-5.641634	0.00353453052	0.0051082826744376919	0
 25	1	1.07475233	0.7454996	0.42372049536525624	1
 26	0	-5.05423546	0.00634177	0.0091783743058498103	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-2.63470244	0.06693815	0.099955373797007113	0
 38	1	3.11990023	0.9577062	0.062344933763709205	1
 39	1	1.3332	0.791369438	0.33757674381727276	1
-40	0				
+40	0				0
 41	1	1.76657629	0.8540314	0.22763900783247884	1
 42	1	5.77468061	0.996904433	0.0044728861234643764	1
 43	1	-0.160024166	0.4600791	1.1200461625954479	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.98228741	0.00681164	0.0098607417433267518	0
 137	0	-5.97203064	0.00254257885	0.0036728371153443573	0
 138	0	-4.3374877	0.0129007176	0.018732896643962105	0
-139	0				
+139	0				0
 140	0	-5.97203064	0.00254257885	0.0036728371153443573	0
 141	0	-5.97203064	0.00254257885	0.0036728371153443573	0
 142	1	3.62155676	0.973955452	0.03807230821683618	1
 143	0	-4.06941748	0.0168002676	0.024443571870852193	0
 144	0	-5.531984	0.003942524	0.0056991017626305011	0
-145	0				
+145	0				0
 146	1	0.845272541	0.69957453	0.51545032982981998	1
 147	0	-5.264244	0.00514667667	0.0074442579843589417	0
 148	0	-3.53539133	0.0283218417	0.041449555087460649	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.63197279	0.9328912	0.1002192761113103	1
 156	0	-4.95913267	0.00697009	0.010090922390098837	0
 157	0	-5.091937	0.006108559	0.0088398149066821179	0
-158	0				
+158	0				0
 159	1	7.637605	0.9995183	0.00069514934090023593	1
 160	1	5.102776	0.9939569	0.00874476585784471	1
 161	0	-4.27338028	0.013743096	0.019964600611336557	0
 162	0	-5.091937	0.006108559	0.0088398149066821179	0
 163	0	-3.67683315	0.0246785376	0.036050290649489301	0
-164	0				
+164	0				0
 165	0	-3.45594358	0.0305921026	0.044824259180207618	0
 166	1	4.88854	0.9925239	0.010826239558709188	1
 167	1	2.59618044	0.930615366	0.10374308707957469	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.465872765	0.6144064	1.3748470144034199	1
 233	1	3.621717	0.9739595	0.038066304453576054	1
 234	0	-3.43166828	0.0313202776	0.045908353174351067	0
-235	0				
+235	0				0
 236	1	6.647678	0.9987047	0.001869974861439897	1
 237	1	4.42246	0.9881377	0.017215962974508822	1
 238	1	6.44672251	0.9984168	0.0022859116128351314	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	6.46864176	0.998451054	0.0022363890442921863	1
 247	1	1.5234189	0.8210414	0.28447311579312373	1
 248	0	-4.00451946	0.0179065578	0.026067797200325149	0
-249	0				
+249	0				0
 250	0	-5.39917946	0.00449994765	0.0065067030783201637	0
 251	1	4.104112	0.983763337	0.023616805142920666	1
 252	0	2.75052214	0.939942837	4.0575198580425882	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.62500715	0.8354845	0.2593150232737797	1
 273	1	0.228233814	0.556812048	0.84473766721050514	1
 274	0	-4.82307673	0.007977848	0.011555758238394069	0
-275	0				
+275	0				0
 276	0	-5.531984	0.003942524	0.0056991017626305011	0
 277	0	-6.0816803	0.00227912888	0.003291840622802274	0
 278	0	-5.641634	0.00353453052	0.0051082826744376919	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	5.68027353	0.996598959	0.004915027880645002	1
 290	0	-6.521727	0.00146896509	0.0021208267355545722	0
 291	0	-5.641634	0.00353453052	0.0051082826744376919	0
-292	1				
+292	1				0
 293	1	2.365685	0.9141729	0.12946106222132911	1
-294	0				
+294	0				0
 295	1	4.049787	0.982872367	0.024924010557578272	1
 296	0	1.7836585	0.856148	2.7973428610745215	1
-297	0				
+297	0				0
 298	0	-3.845192	0.0209346656	0.030522958750931656	0
 299	1	2.974937	0.95142895	0.071832170969213474	1
 300	1	4.1471324	0.9844364	0.022630102350657457	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.437553883	0.607676	0.71862571139451958	1
 313	0	-6.521727	0.00146896509	0.0021208267355545722	0
 314	0	-6.0816803	0.00227912888	0.003291840622802274	0
-315	0				
+315	0				0
 316	1	3.03096247	0.953953445	0.068009233653927595	1
 317	1	3.97896051	0.9816384	0.026736450275361392	1
 318	0	-5.641634	0.00353453052	0.0051082826744376919	0
 319	0	1.61403608	0.833970964	2.5904925250318187	1
 320	1	5.17757845	0.99439	0.0081162910482616441	1
-321	0				
+321	0				0
 322	0	-5.091937	0.006108559	0.0088398149066821179	0
 323	1	3.22697878	0.961837	0.056135679390163992	1
 324	0	-5.641634	0.00353453052	0.0051082826744376919	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-2.996994	0.0475618578	0.070302697725435973	0
 409	0	-4.887184	0.007486166	0.010840883662554117	0
 410	0	-6.0816803	0.00227912888	0.003291840622802274	0
-411	0				
+411	0				0
 412	1	4.5649085	0.989696443	0.014942001227255185	1
 413	0	-3.34774446	0.0339691	0.049858759088118251	0
 414	1	3.84952021	0.9791539	0.030392501392593196	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-5.531984	0.003942524	0.0056991017626305011	0
 615	0	-3.69268847	0.02429977	0.035490127405006046	0
 616	0	-5.531984	0.003942524	0.0056991017626305011	0
-617	0				
+617	0				0
 618	0	-4.98228741	0.00681164	0.0098607417433267518	0
 619	0	-4.43259048	0.0117441025	0.01704343535923129	0
 620	0	-5.531984	0.003942524	0.0056991017626305011	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt
index c637c69d47..92061b497a 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	7.291877	0.999319434	0.00098218321186686951	1
 35	0	-5.869519	0.002816277	0.0040687610645090766	0
 37	0	-1.02334213	0.2643769	0.44296132773823416	0
-40	0				
+40	0				0
 41	1	2.78505516	0.9418629	0.086411051010362436	1
 44	1	7.821086	0.999599	0.00057866567352766714	1
 45	0	-5.776886	0.00308877858	0.0044630618032660361	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.724151	0.008800117	0.01275207813790242	0
 141	0	-6.55827045	0.00141632778	0.0020447774455947432	0
 144	0	-5.869519	0.002816277	0.0040687610645090766	0
-145	0				
+145	0				0
 147	0	-5.710598	0.00329976762	0.0047684300667823433	0
 150	0	-5.60911131	0.003650946	0.0052768404018184306	0
 151	1	5.118675	0.994051635	0.0086073014434059885	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-6.9242	0.000982723	0.0014184666437026428	0
 156	0	-5.82082272	0.00295639853	0.0042714987401086318	0
 161	0	-4.27493	0.0137221068	0.019933897944770858	0
-164	0				
+164	0				0
 167	1	8.728978	0.9998382	0.00023348534112652949	1
 169	0	-6.667038	0.00127054506	0.0018341745113224558	0
 171	0	-5.546697	0.00388516486	0.0056160247410976614	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	11.3055124	0.9999877	1.7714321792245208E-05	1
 247	1	2.306137	0.909384	0.1370384544406823	1
 248	0	-3.57901382	0.027145749	0.039704412233602736	0
-249	0				
+249	0				0
 250	0	-6.50957441	0.00148689921	0.0021467385111997687	0
 252	0	4.227894	0.9856265	6.1204466632636887	1
 254	1	5.1967	0.9944957	0.0079629764358839714	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.546697	0.00388516486	0.0056160247410976614	0
 271	0	-4.08297968	0.01657771	0.024117038815588843	0
 272	1	4.140359	0.984332263	0.022782712303270784	1
-275	0				
+275	0				0
 276	0	-5.50359	0.004055611	0.0058629065586406487	0
 277	0	-6.235449	0.00195492059	0.002823114622841595	0
 278	0	-5.546697	0.00388516486	0.0056160247410976614	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.546697	0.00388516486	0.0056160247410976614	0
 293	1	4.409566	0.9879857	0.017437977320811163	1
 296	0	1.50613689	0.818488	2.4618631795162846	1
-297	0				
+297	0				0
 299	1	7.93633366	0.9996426	0.00051569614495754321	1
 300	1	7.85100842	0.9996108	0.00056163266102194308	1
 301	0	-5.546697	0.00388516486	0.0056160247410976614	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	3.280983	0.9637706	0.05323826093940856	1
 317	1	9.331164	0.999911368	0.00012787476790525535	1
 319	0	2.956067	0.9505495	4.3378705942158717	1
-321	0				
+321	0				0
 323	1	5.71478939	0.996714	0.0047485078589307303	1
 327	0	-6.235449	0.00195492059	0.002823114622841595	0
 328	1	1.37423134	0.7980629	0.32542559954710693	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	18.5483551	1	0	1
 613	0	-5.86728668	0.00282255374	0.0040778419569695535	0
 614	0	-5.931934	0.00264632422	0.0038228993852335589	0
-617	0				
+617	0				0
 618	0	-5.1376605	0.00583713735	0.0084458830416492391	0
 619	0	-4.771732	0.00839464	0.012162025043583415	0
 621	0	0.3424616	0.5847883	1.2680810757859888	1
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.595036	0.01000083	0.014500778622910757	0
 19	0	-3.32248163	0.03480794	0.051112046016137037	0
 22	0	-5.58065033	0.00375595246	0.0054288957255828087	0
-23	1				
+23	1				0
 24	0	-6.503868	0.00149539544	0.0021590142749859306	0
 26	0	-5.548387	0.00387863023	0.0056065605311466102	0
 27	0	-4.308096	0.0132804094	0.01928794203033625	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.58065033	0.00375595246	0.0054288957255828087	0
 135	0	-3.21473217	0.038615074	0.056813911931726302	0
 136	0	-4.944373	0.007072995	0.010240432848577178	0
-139	0				
+139	0				0
 140	0	-5.929988	0.00265146513	0.0038303358354253489	0
 142	1	3.36657238	0.966643333	0.048944424422816823	1
 143	0	-5.92445755	0.0026661302	0.0038515494632620751	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.654668	0.009427353	0.013665310686569912	0
 155	1	1.85960007	0.865250349	0.20881047650865889	1
 157	0	-5.867591	0.00282169762	0.0040766033438554457	0
-158	0				
+158	0				0
 159	1	9.591543	0.9999317	9.8549424786689596E-05	1
 160	1	7.363619	0.9993665	0.00091420540184684017	1
 162	0	-5.231313	0.00531806657	0.0076928219174680146	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.973879	0.9974621	0.0036660786976757281	1
 232	0	1.10679436	0.751531	2.008862256839882	1
 234	0	-3.7641573	0.0226616841	0.033070042201646284	0
-235	0				
+235	0				0
 236	1	8.480452	0.9997926	0.00029928085261473974	1
 238	1	9.448584	0.9999212	0.00011368501131740873	1
 243	0	-4.52710867	0.0106962454	0.015514542524251164	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	11.9692574	0.9999937	9.115109290810302E-06	1
 287	0	-5.58065033	0.00375595246	0.0054288957255828087	0
 289	1	5.61943245	0.9963864	0.005222752234881816	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	5.155699	0.9942666	0.008295308421383105	1
 298	0	-2.71633816	0.0620161332	0.092364986128816551	0
 302	1	12.1483784	0.9999947	7.6532482629398447E-06	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-6.503868	0.00149539544	0.0021590142749859306	0
 310	0	-6.216928	0.001991392	0.00287583593610438	0
 313	0	-7.2025423	0.000744136	0.0010739609416730365	0
-315	0				
+315	0				0
 318	0	-6.503868	0.00149539544	0.0021590142749859306	0
 320	1	4.269491	0.9862041	0.02004186218454097	1
 322	0	-5.231313	0.00531806657	0.0076928219174680146	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-6.853205	0.00105495122	0.0015227762658880663	0
 408	0	-4.852546	0.00774797052	0.011221486878031036	0
 410	0	-6.853205	0.00105495122	0.0015227762658880663	0
-411	0				
+411	0				0
 412	1	7.587702	0.9994936	0.00073076734716613276	1
 417	0	-6.853205	0.00105495122	0.0015227762658880663	0
 420	0	-3.639381	0.0255962238	0.037408370576337828	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt
index a0df8ed00a..4ee5047adb 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-non-negative-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	6.59719467	0.9986377	0.0019667577188335239	1
 21	1	6.9093914	0.999002635	0.0014396108762453246	1
 22	0	-5.50264263	0.00405943953	0.0058684526611357517	0
-23	1				
+23	1				0
 24	0	-6.14459133	0.002140461	0.0030913421022840675	0
 25	1	0.9981127	0.7306873	0.4526739227114121	1
 26	0	-5.56536674	0.00381357735	0.0055123467049374769	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.79816341	0.142074779	0.22107619020053021	0
 38	1	4.925646	0.9927943	0.010433298358924143	1
 39	1	0.895828247	0.7100915	0.49392321501990555	1
-40	0				
+40	0				0
 41	1	2.72234154	0.93833214	0.091829412491125792	1
 42	1	6.45601654	0.998431444	0.0022647243580549464	1
 43	1	-0.5776577	0.359471738	1.4760497444221736	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.965955	0.006923029	0.010022553277705419	0
 137	0	-5.93407059	0.00264069065	0.0038147503192492542	0
 138	0	-4.668453	0.009299485	0.013479092815885742	0
-139	0				
+139	0				0
 140	0	-5.93407059	0.00264069065	0.0038147503192492542	0
 141	0	-6.47075844	0.00154565845	0.0022316389032971582	0
 142	1	3.64823437	0.9746237	0.037082819238846716	1
 143	0	-5.466771	0.00420707744	0.0060823331671915537	0
 144	0	-6.03933048	0.002377488	0.0034340739321673348	0
-145	0				
+145	0				0
 146	1	-0.110341072	0.4724427	1.0817887726099731	0
 147	0	-6.11751556	0.002199078	0.0031760924132441036	0
 148	0	-1.55709267	0.174064219	0.2758984827724662	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.36491013	0.9141121	0.12955701132443528	1
 156	0	-6.267907	0.00189260417	0.002733037741461919	0
 157	0	-5.607903	0.003655344	0.0052832085489667481	0
-158	0				
+158	0				0
 159	1	10.9176846	0.9999819	2.614159977229895E-05	1
 160	1	7.75989342	0.9995737	0.00061514108379339587	1
 161	0	-4.309515	0.0132618267	0.019260772318565499	0
 162	0	-5.07121468	0.006235666	0.0090243302579491296	0
 163	0	-3.76092339	0.02273342	0.033175939048272665	0
-164	0				
+164	0				0
 165	0	-3.924346	0.0193723515	0.028222656292276067	0
 166	1	6.74228859	0.998821437	0.001701309224545778	1
 167	1	7.94067574	0.99964416	0.0005134595729021004	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.7225275	0.673163354	1.6133583443719168	1
 233	1	5.29774761	0.995022058	0.0071995859979441072	1
 234	0	-3.554101	0.027811477	0.040691992083778071	0
-235	0				
+235	0				0
 236	1	10.4206543	0.9999702	4.2996303413732479E-05	1
 237	1	5.828807	0.997067034	0.0042375925496323883	1
 238	1	11.3587952	0.9999883	1.6854398235588073E-05	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.599171	0.9999322	9.7775450197580527E-05	1
 247	1	2.067935	0.887747347	0.17177895049852415	1
 248	0	-3.4094696	0.0320008248	0.046922276673100262	0
-249	0				
+249	0				0
 250	0	-6.699335	0.0012302153	0.0017759181240158319	0
 251	1	7.9959507	0.9996633	0.00048584679587356108	1
 252	0	3.6111412	0.9736899	5.2482402117884597	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.72366619	0.848600447	0.23684265601696217	1
 273	1	-0.342484474	0.4152061	1.2681004399882052	0
 274	0	-4.846204	0.007796883	0.011292605602753639	0
-275	0				
+275	0				0
 276	0	-5.50264263	0.00405943953	0.0058684526611357517	0
 277	0	-6.57601929	0.0013914461	0.0020088303041534395	0
 278	0	-6.14459133	0.002140461	0.0030913421022840675	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	7.101452	0.999176741	0.0011882013529343118	1
 290	0	-7.007447	0.0009042981	0.0013052166206428517	0
 291	0	-6.14459133	0.002140461	0.0030913421022840675	0
-292	1				
+292	1				0
 293	1	4.6855	0.9908563	0.013252265463070151	1
-294	0				
+294	0				0
 295	1	6.2168417	0.99800843	0.0028760930785605436	1
 296	0	1.02090549	0.735148966	1.9167469555439196	1
-297	0				
+297	0				0
 298	0	-3.02001572	0.0465297773	0.068740211727588499	0
 299	1	7.09773827	0.9991737	0.0011925905306341051	1
 300	1	6.64691544	0.998703659	0.001871438610749495	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	2.90730953	0.9482066	0.076726654530730437	1
 313	0	-7.007447	0.0009042981	0.0013052166206428517	0
 314	0	-6.649353	0.001293185	0.0018668790298154393	0
-315	0				
+315	0				0
 316	1	2.12067223	0.892896235	0.16343556787762994	1
 317	1	7.5715065	0.9994854	0.00074264021133653045	1
 318	0	-5.92458725	0.00266578537	0.0038510506602204577	0
 319	0	1.35382557	0.7947544	2.2845767018893883	1
 320	1	5.988476	0.9974988	0.0036129742419820916	1
-321	0				
+321	0				0
 322	0	-5.07121468	0.006235666	0.0090243302579491296	0
 323	1	4.28225327	0.986376643	0.019789456912749203	1
 324	0	-6.14459133	0.002140461	0.0030913421022840675	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-4.58592224	0.0100914678	0.014632868867702545	0
 409	0	-5.205141	0.00545831956	0.0078962603748794508	0
 410	0	-6.57601929	0.0013914461	0.0020088303041534395	0
-411	0				
+411	0				0
 412	1	7.70175171	0.9995482	0.00065196153701951257	1
 413	0	-3.70033741	0.02411908	0.035222977147123087	0
 414	1	5.41945839	0.99559	0.006376396588275309	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.112665	0.00220974674	0.003191518193469859	0
 615	0	-4.37095165	0.012481451	0.018120247723782505	0
 616	0	-5.50264263	0.00405943953	0.0058684526611357517	0
-617	0				
+617	0				0
 618	0	-4.965955	0.006923029	0.010022553277705419	0
 619	0	-4.429267	0.0117827384	0.017099838701332234	0
 620	0	-5.50264263	0.00405943953	0.0058684526611357517	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt
index 4a5221f10c..43409b9917 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	4.28022528	0.9863494	0.019829298264044417	1
 35	0	-4.29419041	0.0134638669	0.019556202484947195	0
 37	0	-1.95759869	0.123727158	0.19054794774570458	0
-40	0				
+40	0				0
 41	1	1.34579754	0.7934417	0.33380384997661361	1
 44	1	5.22175264	0.9946311	0.0077665361772382407	1
 45	0	-4.55969143	0.0103568994	0.015019761369081966	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-3.50701833	0.0291131958	0.042624993467054707	0
 141	0	-4.510108	0.0108776484	0.015779105577069866	0
 144	0	-4.29419041	0.0134638669	0.019556202484947195	0
-145	0				
+145	0				0
 147	0	-4.118532	0.0160079524	0.023281438797448952	0
 150	0	-4.43784046	0.0116833262	0.016954714516170224	0
 151	1	2.86513376	0.9460957	0.079941963974142813	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-4.792855	0.008220622	0.011908867541972762	0
 156	0	-4.152423	0.0154827805	0.022511655407603286	0
 161	0	-3.361469	0.0335215963	0.049190599682179155	0
-164	0				
+164	0				0
 167	1	3.00652266	0.9528679	0.069651835538374979	1
 169	0	-4.76463461	0.008453925	0.012248282163630898	0
 171	0	-4.36102	0.0126044592	0.01829996516606797	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	7.761687	0.9995744	0.00061410874818056485	1
 247	1	2.24705172	0.904395938	0.14497358262585658	1
 248	0	-2.75623083	0.05973572	0.088861781570551343	0
-249	0				
+249	0				0
 250	0	-4.36834049	0.0125136767	0.018167327858314108	0
 252	0	2.47272253	0.9222073	3.6842213333365441	1
 254	1	5.30986643	0.9950817	0.0071130806432035459	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-4.36102	0.0126044592	0.01829996516606797	0
 271	0	-3.23003125	0.0380511023	0.055967840193562365	0
 272	1	1.97665262	0.878323853	0.18717511071531998	1
-275	0				
+275	0				0
 276	0	-4.011443	0.0177852046	0.025889540399059593	0
 277	0	-4.57693768	0.010181617	0.014764258553784819	0
 278	0	-4.36102	0.0126044592	0.01829996516606797	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-4.36102	0.0126044592	0.01829996516606797	0
 293	1	3.50341845	0.9707849	0.042776422691022505	1
 296	0	0.854511261	0.701512635	1.7442582303419563	1
-297	0				
+297	0				0
 299	1	4.02451658	0.9824417	0.025556263019683039	1
 300	1	4.165831	0.9847203	0.02221411037855156	1
 301	0	-4.36102	0.0126044592	0.01829996516606797	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	2.756329	0.940269768	0.088853362072482428	1
 317	1	5.80636454	0.9970007	0.004333585623359653	1
 319	0	1.0757966	0.7456977	1.975383454841898	1
-321	0				
+321	0				0
 323	1	3.082415	0.956161559	0.064673689924879513	1
 327	0	-4.57693768	0.010181617	0.014764258553784819	0
 328	1	2.805962	0.942997158	0.084674672619554123	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	9.154173	0.999894261	0.00015255667702522208	1
 613	0	-3.88851619	0.0200648643	0.029241838018723456	0
 614	0	-4.371011	0.0124807227	0.018119183737570529	0
-617	0				
+617	0				0
 618	0	-3.72869563	0.0234605316	0.034249740786795546	0
 619	0	-3.44594836	0.0308899172	0.045267541796380997	0
 621	0	-0.782016754	0.3138854	0.54347850919806506	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-3.6590457	0.0251103118	0.036689112229595131	0
 19	0	-2.927483	0.0508115776	0.075233591312011905	0
 22	0	-4.14026976	0.0156691261	0.022784748886103094	0
-23	1				
+23	1				0
 24	0	-4.75638962	0.008523319	0.012349253326730132	0
 26	0	-3.93837214	0.0191076845	0.027833331950969452	0
 27	0	-3.40870714	0.03202445	0.046957488715061987	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-4.14026976	0.0156691261	0.022784748886103094	0
 135	0	-2.62711	0.06741392	0.1006911970043132	0
 136	0	-3.77448845	0.0224339925	0.032733975062274864	0
-139	0				
+139	0				0
 140	0	-4.255713	0.0139846308	0.020317960583175827	0
 142	1	1.9862442	0.879345238	0.18549840430247841	1
 143	0	-3.74331784	0.02312786	0.033758349764067219	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-3.267953	0.0366871059	0.053923618256310278	0
 155	1	1.88906479	0.8686489	0.20315494639328185	1
 157	0	-4.39060831	0.0122414771	0.017769705367455636	0
-158	0				
+158	0				0
 159	1	6.88715744	0.9989802	0.001471976257367614	1
 160	1	5.57244873	0.996213257	0.0054734847881935346	1
 162	0	-4.024827	0.0175529048	0.025548374564996635	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	4.531541	0.989350557	0.015446292097008558	1
 232	0	0.251759052	0.562609434	1.1930059918223119	1
 234	0	-2.51516485	0.0748018846	0.11216576762239737	0
-235	0				
+235	0				0
 236	1	5.772835	0.9968987	0.0044811669482472481	1
 238	1	6.65452766	0.9987135	0.0018572316949005939	1
 243	0	-3.28154564	0.036209736	0.053208867556931244	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	8.09413	0.999694765	0.00044042879818134223	1
 287	0	-4.14026976	0.0156691261	0.022784748886103094	0
 289	1	4.30420876	0.9866685	0.019362604522295365	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	3.601099	0.973431468	0.038848681676236112	1
 298	0	-2.22490883	0.09753586	0.14805849380018501	0
 302	1	8.018049	0.9996706	0.00047526633912005399	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-4.75638962	0.008523319	0.012349253326730132	0
 310	0	-4.506051	0.0109213842	0.015842898366274911	0
 313	0	-4.987275	0.00677798	0.0098118479335557937	0
-315	0				
+315	0				0
 318	0	-4.75638962	0.008523319	0.012349253326730132	0
 320	1	2.81792259	0.943636656	0.08369663336324043	1
 322	0	-4.024827	0.0175529048	0.025548374564996635	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-4.87183237	0.00760109862	0.011007956774122585	0
 408	0	-3.31706572	0.03499035	0.051384728090851442	0
 410	0	-4.87183237	0.00760109862	0.011007956774122585	0
-411	0				
+411	0				0
 412	1	5.23884	0.9947216	0.007635302704268032	1
 417	0	-4.87183237	0.00760109862	0.011007956774122585	0
 420	0	-2.70138979	0.0628913939	0.093711836328273818	0
diff --git a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt
index ff73fc5189..3b2e2b7470 100644
--- a/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/LogisticRegression/LogisticRegression-norm-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	3.96267843	0.9813426	0.027171185979008489	1
 21	1	5.265054	0.9948575	0.0074382155674881083	1
 22	0	-4.51155567	0.0108620832	0.015756402974357524	0
-23	1				
+23	1				0
 24	0	-5.107146	0.00601691334	0.0087067913827365544	0
 25	1	0.6726794	0.6621029	0.59487269328676762	1
 26	0	-4.36255264	0.0125854	0.018272117354929882	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-2.04001045	0.115065664	0.17635768683092809	0
 38	1	3.6194644	0.973902345	0.038150977482211336	1
 39	1	0.673018932	0.6621788	0.59470724065030856	1
-40	0				
+40	0				0
 41	1	1.75375986	0.8524264	0.23035280375662126	1
 42	1	5.60796976	0.9963449	0.0052828205055256471	1
 43	1	-0.5184488	0.37321502	1.4219210475645763	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-4.10382557	0.0162412636	0.023623552162962799	0
 137	0	-4.73142624	0.008736885	0.01266004645418743	0
 138	0	-3.874074	0.0203508064	0.029662873497674963	0
-139	0				
+139	0				0
 140	0	-4.73142624	0.008736885	0.01266004645418743	0
 141	0	-5.13915634	0.00582846347	0.0084332958699167727	0
 142	1	2.53462648	0.9265339	0.11008436686792368	1
 143	0	-4.1287837	0.0158472732	0.02304587572398243	0
 144	0	-4.919286	0.00725137955	0.010499643937654568	0
-145	0				
+145	0				0
 146	1	0.185849667	0.546329141	0.87215771785369722	1
 147	0	-4.93812275	0.007117027	0.010304411526052911	0
 148	0	-2.08798218	0.110270388	0.16856112656874939	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.24833822	0.9045071	0.14479626651911345	1
 156	0	-4.913893	0.007290303	0.010556209568305783	0
 157	0	-4.69941568	0.009018519	0.013069997580773615	0
-158	0				
+158	0				0
 159	1	8.213823	0.9997292	0.0003907114930137318	1
 160	1	6.409885	0.9983575	0.0023716112041259128	1
 161	0	-3.70981741	0.0238969475	0.034894625912887001	0
 162	0	-4.29168558	0.0134971775	0.019604916230060426	0
 163	0	-4.20999336	0.0146292737	0.021261482597556794	0
-164	0				
+164	0				0
 165	0	-3.35529184	0.0337223038	0.049490233625727506	0
 166	1	5.13335562	0.9941378	0.0084822193431077515	1
 167	1	4.31503153	0.986810148	0.019155543364578753	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.387140751	0.5955942	1.3061245037640643	1
 233	1	4.22282743	0.9855546	0.020992330945643928	1
 234	0	-2.79013348	0.0578596778	0.085986144354393876	0
-235	0				
+235	0				0
 236	1	7.198673	0.999253	0.0010781320275837761	1
 237	1	4.24964952	0.9859315	0.020440656601130012	1
 238	1	7.93097258	0.9996407	0.00051844885378563097	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	8.043116	0.9996788	0.00046348169408102081	1
 247	1	2.170814	0.8975978	0.15585897141376154	1
 248	0	-3.01326466	0.0468302034	0.069194857755858583	0
-249	0				
+249	0				0
 250	0	-5.133764	0.005859794	0.0084787621145538308	0
 251	1	5.4693675	0.9958038	0.0060666126630314994	1
 252	0	2.521253	0.925618351	3.7489094481346643	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.26803923	0.7804069	0.35770157547115156	1
 273	1	-0.341918468	0.415343523	1.2676230380461255	0
 274	0	-4.11754751	0.01602347	0.023304190486054636	0
-275	0				
+275	0				0
 276	0	-4.51155567	0.0108620832	0.015756402974357524	0
 277	0	-5.327016	0.00483505568	0.0069924288920724343	0
 278	0	-5.107146	0.00601691334	0.0087067913827365544	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	5.13687468	0.9941583	0.0084524642023233402	1
 290	0	-5.54688644	0.00388443237	0.005614963867042919	0
 291	0	-5.107146	0.00601691334	0.0087067913827365544	0
-292	1				
+292	1				0
 293	1	3.96790457	0.981438041	0.027030903251222888	1
-294	0				
+294	0				0
 295	1	4.55162954	0.9895601	0.015140724489837425	1
 296	0	0.6700988	0.661525249	1.5628798789895393	1
-297	0				
+297	0				0
 298	0	-2.40630245	0.08269336	0.12452401321321592	0
 299	1	4.497334	0.988984048	0.015980843395464565	1
 300	1	4.62145948	0.990257442	0.014124456553393392	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	1.84912252	0.864024043	0.21085663625525078	1
 313	0	-5.54688644	0.00388443237	0.005614963867042919	0
 314	0	-5.36138344	0.004672473	0.0067567510712633252	0
-315	0				
+315	0				0
 316	1	2.20764112	0.900933564	0.15050737158003294	1
 317	1	5.890983	0.997243345	0.0039825045312741787	1
 318	0	-5.00404263	0.006666029	0.0096492437155483984	0
 319	0	0.6469283	0.656317949	1.540853588056835	1
 320	1	3.99139547	0.9818612	0.026409039376297374	1
-321	0				
+321	0				0
 322	0	-4.29168558	0.0134971775	0.019604916230060426	0
 323	1	3.157802	0.959215045	0.060073807756361522	1
 324	0	-5.107146	0.00601691334	0.0087067913827365544	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-3.57900143	0.0271460768	0.039704898382857935	0
 409	0	-4.281804	0.0136293843	0.019798272915656116	0
 410	0	-5.327016	0.00483505568	0.0069924288920724343	0
-411	0				
+411	0				0
 412	1	6.193191	0.997960865	0.0029448527311883681	1
 413	0	-3.24647379	0.0374538042	0.055072312735252281	0
 414	1	4.55400229	0.9895846	0.015105009633995839	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-4.95365334	0.00700811762	0.010146170993954725	0
 615	0	-3.64432216	0.0254732724	0.037226341208279841	0
 616	0	-4.51155567	0.0108620832	0.015756402974357524	0
-617	0				
+617	0				0
 618	0	-4.10382557	0.0162412636	0.023623552162962799	0
 619	0	-3.696096	0.0242191125	0.035370869193417386	0
 620	0	-4.51155567	0.0108620832	0.015756402974357524	0
diff --git a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-CV-breast-cancer.txt
index 7cfbe77b4a..5c9bde6605 100644
--- a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	0.8960438	0.7101358	0.49383312022081494	1
 35	0	-1.47149158	0.186716	0.298168872554196	0
 37	0	-1.077555	0.253969	0.42269254099397019	0
-40	0				
+40	0				0
 41	1	-0.110265851	0.472461432	1.0817315302478872	0
 44	1	1.38623238	0.799990058	0.32194602419012386	1
 45	0	-1.49285364	0.1834938	0.29246424185161274	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.329715	0.2092065	0.33862709419515019	0
 141	0	-1.51333463	0.18044512	0.28708753442168577	0
 144	0	-1.47149158	0.186716	0.298168872554196	0
-145	0				
+145	0				0
 147	0	-1.36272907	0.203797117	0.3287919993163349	0
 150	0	-1.490515	0.183844447	0.29308395009459498	0
 151	1	0.488354921	0.6197188	0.69031438298058734	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-1.54631257	0.175619483	0.27861768553552435	0
 156	0	-1.34795034	0.206205666	0.33316283039965772	0
 161	0	-1.29642129	0.214767918	0.34880897708810421	0
-164	0				
+164	0				0
 167	1	0.7817354	0.686054	0.54360597630084673	1
 169	0	-1.52040219	0.1794023	0.28525299602441972	0
 171	0	-1.46262646	0.188065946	0.3005655398637459	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.30008841	0.908884346	0.13783136852928218	1
 247	1	0.283135176	0.5703147	0.81016986229628651	1
 248	0	-1.02733588	0.263600916	0.44144026210768955	0
-249	0				
+249	0				0
 250	0	-1.3897934	0.199440747	0.32091990872905618	0
 252	0	0.575369835	0.6400013	1.4739363860396681	1
 254	1	1.36448383	0.796487451	0.32827646395944027	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.46262646	0.188065946	0.3005655398637459	0
 271	0	-1.330715	0.209041134	0.33832542505991492	0
 272	1	0.3417368	0.58461237	0.77444774011663531	1
-275	0				
+275	0				0
 276	0	-1.43851376	0.1917756	0.30717219734355156	0
 277	0	-1.50446939	0.181759879	0.28940381583950159	0
 278	0	-1.46262646	0.188065946	0.3005655398637459	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.46262646	0.188065946	0.3005655398637459	0
 293	1	0.690094	0.665987849	0.58643223892348229	1
 296	0	0.122398376	0.530561447	1.090991766168943	1
-297	0				
+297	0				0
 299	1	0.8090725	0.6919118	0.53133991521179469	1
 300	1	1.07804394	0.7461236	0.42251343016986392	1
 301	0	-1.46262646	0.188065946	0.3005655398637459	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.633879662	0.653368652	0.61403085786632716	1
 317	1	1.75457263	0.852528632	0.2301798078479787	1
 319	0	0.1361382	0.5339821	1.1015427183713855	1
-321	0				
+321	0				0
 323	1	0.8411846	0.6987147	0.51722465664834216	1
 327	0	-1.50446939	0.181759879	0.28940381583950159	0
 328	1	0.758497	0.681027353	0.55421535102487163	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	2.80018759	0.942685962	0.085150850944065576	1
 613	0	-1.31009483	0.212470978	0.34459500515903269	0
 614	0	-1.49938011	0.18251799	0.29074111357003468	0
-617	0				
+617	0				0
 618	0	-1.40553582	0.196939126	0.31641874253214702	0
 619	0	-1.37255788	0.2022069	0.32591343959007929	0
 621	0	-0.609831333	0.35209766	0.62615172722986678	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.29125416	0.2156406	0.35041324245427652	0
 19	0	-1.18682528	0.233827218	0.38425832019246531	0
 22	0	-1.38527489	0.200163171	0.32222238184143043	0
-23	1				
+23	1				0
 24	0	-1.44789767	0.19032532	0.30458573193898042	0
 26	0	-1.321662	0.210541919	0.341065431407162	0
 27	0	-1.28084588	0.217406273	0.35366454853946033	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.36420059	0.203558445	0.3283595980104454	0
 135	0	-0.9835708	0.272183836	0.45835400169661483	0
 136	0	-1.33306038	0.2086536	0.33761874206668624	0
-139	0				
+139	0				0
 140	0	-1.42708111	0.1935539	0.31034997353186378	0
 142	1	0.5200758	0.6271655	0.67308190344279184	1
 143	0	-1.07713079	0.254049361	0.42284792669686094	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.147677	0.240913659	0.39766410362601251	0
 155	1	0.775262833	0.6846582	0.54654409786019487	1
 157	0	-1.39568317	0.198502019	0.31922920878555094	0
-158	0				
+158	0				0
 159	1	2.4702127	0.922027051	0.11711901622998303	1
 160	1	1.8089292	0.8592324	0.21887965615084526	1
 162	0	-1.34346867	0.206940219	0.33449847387485032	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1.80702519	0.859001935	0.21926671447669044	1
 232	0	-0.09305465	0.476753116	0.93443627885443414	0
 234	0	-0.7166654	0.3281277	0.57374106872220532	0
-235	0				
+235	0				0
 236	1	2.0308764	0.884000957	0.1778801634200064	1
 238	1	2.5700233	0.9289072	0.10639359546534205	1
 243	0	-0.9099059	0.2870191	0.48806467358561068	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	3.03633	0.954188645	0.067653576940859037	1
 287	0	-1.36420059	0.203558445	0.3283595980104454	0
 289	1	1.839293	0.8628651	0.21279308434601185	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	1.50403929	0.81817615	0.28951661133253503	1
 298	0	-1.01809835	0.265398	0.44496526256029006	0
 302	1	2.95740485	0.9506123	0.07307101604489151	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.44789767	0.19032532	0.30458573193898042	0
 310	0	-1.4164151	0.1952242	0.31334116395889644	0
 313	0	-1.53151011	0.17777285	0.28239108395025142	0
-315	0				
+315	0				0
 318	0	-1.38467479	0.200259253	0.32239570012101715	0
 320	1	1.03225207	0.737352252	0.43957409861257096	1
 322	0	-1.34346867	0.206940219	0.33449847387485032	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-1.48970389	0.183966175	0.29329914054619283	0
 408	0	-0.969954848	0.2748895	0.46372722780050113	0
 410	0	-1.48970389	0.183966175	0.29329914054619283	0
-411	0				
+411	0				0
 412	1	1.784699	0.8562761	0.22385204529486596	1
 417	0	-1.48970389	0.183966175	0.29329914054619283	0
 420	0	-0.827743053	0.3041225	0.52309474947909951	0
diff --git a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-CV-breast-cancer.txt
index 0302f143a8..98a63fcdf3 100644
--- a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	5.83416653	0.997082651	0.0042149967260249437	1
 35	0	-5.20735168	0.005446332	0.0078788712300762211	0
 37	0	-2.71164179	0.0622898862	0.092786101770516077	0
-40	0				
+40	0				0
 41	1	1.76036549	0.853255451	0.22895036937850363	1
 44	1	7.40955639	0.999394953	0.00087316212305162816	1
 45	0	-5.421812	0.004399689	0.0063614137834035649	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-4.322978	0.0130867995	0.019004890409612719	0
 141	0	-5.4411335	0.00431586	0.0062399450406013428	0
 144	0	-5.20735168	0.005446332	0.0078788712300762211	0
-145	0				
+145	0				0
 147	0	-4.875398	0.00757424766	0.010968922848962245	0
 150	0	-5.39204836	0.00453200564	0.006553162786217457	0
 151	1	4.061223	0.9830638	0.024643020624724253	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-5.73325	0.00322609954	0.0046618015694471927	0
 156	0	-4.91463	0.007284973	0.010548463613035559	0
 161	0	-4.12887526	0.0158458445	0.023043781432081138	0
-164	0				
+164	0				0
 167	1	4.796111	0.9918059	0.011870271192039138	1
 169	0	-5.68914	0.00337109854	0.0048716832359580091	0
 171	0	-5.265687	0.005139294	0.0074335520922891698	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	10.8528	0.9999806	2.7947451458241805E-05	1
 247	1	3.03624249	0.95418483	0.06765934462197544	1
 248	0	-3.08702755	0.04364554	0.064382659498109923	0
-249	0				
+249	0				0
 250	0	-5.14841127	0.00577508053	0.0083558311280958943	0
 252	0	3.84936237	0.979150653	5.5838539825714451	1
 254	1	7.35057163	0.9993582	0.00092625186884288718	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-5.265687	0.005139294	0.0074335520922891698	0
 271	0	-4.097221	0.016347127	0.023778810630558714	0
 272	1	2.79984665	0.942667544	0.085179038039461821	1
-275	0				
+275	0				0
 276	0	-4.915235	0.007280598	0.010542105680653375	0
 277	0	-5.49946833	0.00407229364	0.0058870729354622087	0
 278	0	-5.265687	0.005139294	0.0074335520922891698	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-5.265687	0.005139294	0.0074335520922891698	0
 293	1	4.736758	0.991309166	0.012593024732102163	1
 296	0	1.75365162	0.85241276	2.760360102190484	1
-297	0				
+297	0				0
 299	1	5.53140068	0.9960552	0.0057024187918531082	1
 300	1	6.04150867	0.9976277	0.0034266068641119179	1
 301	0	-5.265687	0.005139294	0.0074335520922891698	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	4.025776	0.9824635	0.025524315591638584	1
 317	1	8.423935	0.9997805	0.00031674081892699212	1
 319	0	1.82892418	0.861633539	2.8534338101579171	1
-321	0				
+321	0				0
 323	1	4.504982	0.9890671	0.015859728309184334	1
 327	0	-5.49946833	0.00407229364	0.0058870729354622087	0
 328	1	4.454892	0.9885119	0.016669732083571809	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	13.2412815	0.9999982	2.5797420694119618E-06	1
 613	0	-4.637956	0.009584702	0.013894495676017315	0
 614	0	-5.333713	0.00480293762	0.0069458679549985972	0
-617	0				
+617	0				0
 618	0	-4.623119	0.009726578	0.014101176192227349	0
 619	0	-4.331002	0.0129835671	0.018853990456118342	0
 621	0	-0.969069	0.2750661	0.46407865469425469	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-4.77261448	0.00838729553	0.012151339639068351	0
 19	0	-4.05630064	0.01701831	0.02476355221691592	0
 22	0	-5.26293468	0.00515338546	0.0074539868149001397	0
-23	1				
+23	1				0
 24	0	-5.847086	0.00287998538	0.0041609352152631573	0
 26	0	-5.01217842	0.00661237258	0.0095713166824383505	0
 27	0	-4.54662037	0.0104917344	0.015216336343473301	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-5.25242233	0.005207562	0.0075325538981779582	0
 135	0	-3.511651	0.028982535	0.042430850287558594	0
 136	0	-4.90477753	0.0073565715	0.010652520453755514	0
-139	0				
+139	0				0
 140	0	-5.39509726	0.00451827142	0.0065332584338255633	0
 142	1	2.2592926	0.9054491	0.14329456494743992	1
 143	0	-4.372905	0.0124574006	0.018085112102952432	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-4.16768646	0.01525183	0.022173264390610525	0
 155	1	2.62865639	0.9326832	0.10054091831709649	1
 157	0	-5.488929	0.004115263	0.0059493194428234175	0
-158	0				
+158	0				0
 159	1	8.939568	0.9998689	0.00018910731810054123	1
 160	1	6.86695	0.9989594	0.0015020181784367139	1
 162	0	-5.13077164	0.00587725034	0.0085040948177142958	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	5.89666176	0.9972589	0.0039599989302112676	1
 232	0	-0.179828167	0.455163717	0.87610531376236689	0
 234	0	-3.15223122	0.04100345	0.060402470875188088	0
-235	0				
+235	0				0
 236	1	7.74873161	0.9995689	0.00062210936850165717	1
 238	1	9.156269	0.99989444	0.00015229867579129541	1
 243	0	-3.844254	0.0209539	0.030551300678084092	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	10.8717079	0.999981	2.7431493603031304E-05	1
 287	0	-5.25242233	0.005207562	0.0075325538981779582	0
 289	1	6.0516243	0.9976515	0.0033921289521523556	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	4.83148575	0.992088437	0.011459363337312383	1
 298	0	-3.31150723	0.0351785272	0.051666079123835182	0
 302	1	10.6722527	0.9999768	3.3451013395372324E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-5.847086	0.00287998538	0.0041609352152631573	0
 310	0	-5.61057949	0.00364560937	0.005269112963217676	0
 313	0	-6.111411	0.00221251347	0.0031955185815049345	0
-315	0				
+315	0				0
 318	0	-5.81555	0.002971982	0.0042940476081927553	0
 320	1	3.90395832	0.98023653	0.028798182473169599	1
 322	0	-5.13077164	0.00587725034	0.0085040948177142958	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-5.97924852	0.002524339	0.0036464555896367997	0
 408	0	-4.06157875	0.01693024	0.024634297974768089	0
 410	0	-5.97924852	0.002524339	0.0036464555896367997	0
-411	0				
+411	0				0
 412	1	6.142968	0.9978561	0.003096342326011223	1
 417	0	-5.97924852	0.002524339	0.0036464555896367997	0
 420	0	-3.33492	0.0343924649	0.050491160716171948	0
diff --git a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt
index 22409b2a5a..85bae57a85 100644
--- a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-L1-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	4.078068	0.983342052	0.024234755458090462	1
 21	1	5.07943726	0.993815064	0.0089506841986991444	1
 22	0	-6.401946	0.00165558141	0.0023904784483303873	0
-23	1				
+23	1				0
 24	0	-6.95376	0.000954126066	0.0013771700453364219	0
 25	1	0.131910324	0.532929838	0.90798248584253316	1
 26	0	-6.20803738	0.00200913986	0.0029014918436988269	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-3.97515774	0.018430287	0.026837360561959296	0
 38	1	3.85910988	0.9793487	0.030105439588229164	1
 39	1	0.289131165	0.5717834	0.806459299491597	1
-40	0				
+40	0				0
 41	1	0.5163593	0.626296043	0.67508333009285992	1
 42	1	6.25112057	0.9980754	0.0027792492014372186	1
 43	1	-1.67306614	0.158015817	2.6618591152960773	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-6.01794958	0.00242874329	0.0035081978824050039	0
 137	0	-6.618124	0.00133415242	0.0019260601909807822	0
 138	0	-5.72209167	0.0032621813	0.0047140259759722502	0
-139	0				
+139	0				0
 140	0	-6.618124	0.00133415242	0.0019260601909807822	0
 141	0	-7.00212	0.00090912357	0.0013121846250039875	0
 142	1	1.86599445	0.8659941	0.20757090594664257	1
 143	0	-5.405919	0.00446985662	0.0064630953185838089	0
 144	0	-6.785942	0.00112826866	0.001628666561573529	0
-145	0				
+145	0				0
 146	1	-0.2344532	0.441653728	1.17901240396708	0
 147	0	-6.632551	0.00131506776	0.0018984903241446914	0
 148	0	-3.505578	0.0291539337	0.042685529480640867	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	2.2497673	0.9046305	0.14459948541676573	1
 156	0	-6.63783455	0.0013081471	0.0018884928122825894	0
 157	0	-6.569764	0.00140016491	0.0020214264686188826	0
-158	0				
+158	0				0
 159	1	9.262019	0.99990505	0.00013699068516156971	1
 160	1	6.81782627	0.9989071	0.001577599187795759	1
 161	0	-5.57644749	0.00377171184	0.005451717595353108	0
 162	0	-6.18576765	0.002054292	0.0029667652410511319	0
 163	0	-5.441502	0.00431427639	0.0062376503223464629	0
-164	0				
+164	0				0
 165	0	-5.081398	0.00617287867	0.0089331816190877534	0
 166	1	5.99673557	0.9975193	0.0035833193575627669	1
 167	1	4.04529858	0.982796669	0.025035126906624509	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.9520569	0.278471351	0.47087141475726779	0
 233	1	4.02608871	0.982468843	0.025516438252352936	1
 234	0	-4.248459	0.0140850125	0.020464842181276369	0
-235	0				
+235	0				0
 236	1	8.120999	0.9997029	0.00042873045458892818	1
 237	1	3.97880173	0.9816355	0.02674065507190734	1
 238	1	9.321572	0.999910533	0.00012907875367543245	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	9.005473	0.9998773	0.00017706700464490148	1
 247	1	1.74156952	0.8508863	0.23296175567699981	1
 248	0	-4.675151	0.009237982	0.013389533098992946	0
-249	0				
+249	0				0
 250	0	-6.85401249	0.00105410081	0.0015215480827833656	0
 251	1	5.57425	0.996220052	0.0054636445480688526	1
 252	0	2.525447	0.9259066	3.7545111242363967	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	1.04092026	0.73902756	0.43629992864352879	1
 273	1	-1.54782867	0.1754001	2.5112785805368674	0
 274	0	-5.9604435	0.002572135	0.0037155870547972859	0
-275	0				
+275	0				0
 276	0	-6.401946	0.00165558141	0.0023904784483303873	0
 277	0	-7.16993856	0.0007687785	0.0011095394740419171	0
 278	0	-6.95376	0.000954126066	0.0013771700453364219	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	5.963811	0.997436464	0.0037031495249571483	1
 290	0	-7.386117	0.0006194141	0.0008939025092919693	0
 291	0	-6.95376	0.000954126066	0.0013771700453364219	0
-292	1				
+292	1				0
 293	1	3.82977867	0.97874707	0.030992011604895862	1
-294	0				
+294	0				0
 295	1	4.92571831	0.992794752	0.010432605435470237	1
 296	0	-0.00817585	0.497956038	0.9941143927175089	0
-297	0				
+297	0				0
 298	0	-4.33488274	0.0129339322	0.018781442391253584	0
 299	1	4.3436203	0.987177134	0.018619117824464626	1
 300	1	4.40119934	0.987885952	0.017583597598896144	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.9174366	0.7145195	0.48495470886222203	1
 313	0	-7.386117	0.0006194141	0.0008939025092919693	0
 314	0	-7.21227646	0.0007369329	0.001063561390310713	0
-315	0				
+315	0				0
 316	1	2.16819382	0.897356749	0.15624644520733796	1
 317	1	6.37115574	0.998292744	0.0024651544582865699	1
 318	0	-6.826747	0.00108320534	0.0015635819620021878	0
 319	0	-0.115743637	0.471096337	0.91892312744499838	0
 320	1	4.11173058	0.9838846	0.023439022974424555	1
-321	0				
+321	0				0
 322	0	-6.18576765	0.002054292	0.0029667652410511319	0
 323	1	3.31629562	0.964983642	0.051423608112212277	1
 324	0	-6.95376	0.000954126066	0.0013771700453364219	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-5.098096	0.00607128069	0.0087857038468610767	0
 409	0	-6.106088	0.00222429563	0.0032125544404639546	0
 410	0	-7.16993856	0.0007687785	0.0011095394740419171	0
-411	0				
+411	0				0
 412	1	6.053849	0.9976567	0.0033846301153950954	1
 413	0	-5.12191772	0.00592920836	0.0085794995279385791	0
 414	1	4.639694	0.9904318	0.013870479681066349	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-6.82828045	0.00108154735	0.0015611874005433336	0
 615	0	-5.42623472	0.00438035838	0.0063334027525860032	0
 616	0	-6.401946	0.00165558141	0.0023904784483303873	0
-617	0				
+617	0				0
 618	0	-6.01794958	0.00242874329	0.0035081978824050039	0
 619	0	-5.633953	0.00356168649	0.0051475999586587254	0
 620	0	-6.401946	0.00165558141	0.0023904784483303873	0
diff --git a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt
index 5197b73592..953068fccb 100644
--- a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	2.322781	0.998222351	0.0025668874786068312	1
 35	0	-1.91525483	0.005915621	0.0085597800780180429	0
 37	0	-0.682821751	0.142692313	0.22211501491184898	0
-40	0				
+40	0				0
 41	1	0.809957266	0.9039319	0.14571398208584879	1
 44	1	2.73944569	0.999422848	0.00083289438051421241	1
 45	0	-1.94671428	0.0054360223	0.0078639160441893435	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.53363073	0.0164193157	0.023884691545080352	0
 141	0	-2.06519866	0.00395226665	0.0057132130161921821	0
 144	0	-1.91525483	0.005915621	0.0085597800780180429	0
-145	0				
+145	0				0
 147	0	-1.84313476	0.007179688	0.010395463465996112	0
 150	0	-1.97708547	0.005009752	0.0072457094989476683	0
 151	1	1.45099306	0.9815549	0.026859095208834581	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-2.1974268	0.00276787742	0.0039987395951823247	0
 156	0	-1.89696681	0.006213517	0.0089921755974289187	0
 161	0	-1.42502642	0.0218984671	0.031943861389482818	0
-164	0				
+164	0				0
 167	1	2.354064	0.998366237	0.0023589497379793915	1
 169	0	-2.21602869	0.00263251015	0.0038029171463890205	0
 171	0	-1.897539	0.006203974	0.008978322239894131	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	3.30174255	0.9998737	0.00018222712667875736	1
 247	1	0.629675865	0.8525092	0.23021269060466767	1
 248	0	-1.12171221	0.0483664	0.07152188601007381	0
-249	0				
+249	0				0
 250	0	-2.04691076	0.00415170472	0.0060021119500057712	0
 252	0	1.01602411	0.942604	4.12290612676055	1
 254	1	2.17657	0.997363031	0.0038093670302838936	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.897539	0.006203974	0.008978322239894131	0
 271	0	-1.368627	0.0254129283	0.037137010195002478	0
 272	1	0.765766859	0.8930476	0.16319106749073262	1
-275	0				
+275	0				0
 276	0	-1.78302681	0.008435549	0.012221545522817861	0
 277	0	-2.047483	0.00414531538	0.0059928556832883097	0
 278	0	-1.897539	0.006203974	0.008978322239894131	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.897539	0.006203974	0.008978322239894131	0
 293	1	1.17371225	0.961760044	0.056251103565820429	1
 296	0	0.4346769	0.773356	2.1415002561411738	1
-297	0				
+297	0				0
 299	1	2.019999	0.9959794	0.0058121507954068162	1
 300	1	2.2421217	0.9977903	0.0031914838554231535	1
 301	0	-1.897539	0.006203974	0.008978322239894131	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.9578371	0.9334789	0.099310694790810672	1
 317	1	2.6748023	0.999312758	0.00099182083151890563	1
 319	0	0.702352047	0.87553966	3.0062420076587428	1
-321	0				
+321	0				0
 323	1	1.138917	0.9581469	0.061681187824867326	1
 327	0	-2.047483	0.00414531538	0.0059928556832883097	0
 328	1	0.998517036	0.9399896	0.089283259387362562	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	5.011583	0.999998748	1.8058189642293044E-06	1
 613	0	-1.848559	0.00707593327	0.010244702155254935	0
 614	0	-1.9948014	0.0047766366	0.006907740990800825	0
-617	0				
+617	0				0
 618	0	-1.6507988	0.0120159388	0.017440327322179375	0
 619	0	-1.51857078	0.017089799	0.024868477463820319	0
 621	0	-0.159297943	0.406589121	0.75289671799437707	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-2.01459932	0.02046752	0.029834763390847389	0
 19	0	-1.722561	0.0706015	0.10563077935630806	0
 22	0	-2.18885	0.009580599	0.013888519789490289	0
-23	1				
+23	1				0
 24	0	-2.45265675	0.00300532184	0.0043422911736604322	0
 26	0	-2.15108967	0.0113010341	0.016396771634848997	0
 27	0	-1.8968116	0.0339725837	0.049863960916695586	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-2.18885	0.009580599	0.013888519789490289	0
 135	0	-1.67432666	0.0859358	0.12963259925365803	0
 136	0	-2.04283071	0.0181100331	0.026366733420336564	0
-139	0				
+139	0				0
 140	0	-2.21708131	0.00846625	0.012266215273071623	0
 142	1	-0.39607358	0.963921666	0.053012185419208942	0
 143	0	-2.12454414	0.0126899984	0.018424952871546458	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-1.87877429	0.03668837	0.053925509586129468	0
 155	1	-0.6914537	0.878659666	0.18662362559522522	0
 157	0	-2.30663776	0.005714676	0.0082681821048535484	0
-158	0				
+158	0				0
 159	1	0.826603651	0.9998317	0.00024285994311160547	1
 160	1	0.465637445	0.999170542	0.0011971518470987805	1
 162	0	-2.16061854	0.0108400183	0.015724220850716938	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	-0.0580048561	0.9916699	0.012068138193505744	0
 232	0	-1.12658465	0.5141482	1.0414117089703063	0
 234	0	-1.83982372	0.04328234	0.063834867527523209	0
-235	0				
+235	0				0
 236	1	0.979896069	0.999914467	0.00012340282955575714	1
 238	1	0.930060863	0.9998934	0.00015376068339360816	1
 243	0	-2.01161838	0.02073334	0.030226326896041298	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	1.41079044	0.999987245	1.8402261006614678E-05	1
 287	0	-2.18885	0.009580599	0.013888519789490289	0
 289	1	0.0753440857	0.9953623	0.0067063762389963991	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	-0.367047548	0.9681271	0.046731673516829733	0
 298	0	-1.44922507	0.202717274	0.32683668378040626	0
 302	1	1.39901066	0.9999866	1.9348177961999343E-05	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-2.45265675	0.00300532184	0.0043422911736604322	0
 310	0	-2.33486915	0.00504769245	0.0073007223089671565	0
 313	0	-2.50911975	0.002343144	0.0033844089083832525	0
-315	0				
+315	0				0
 318	0	-2.45265675	0.00300532184	0.0043422911736604322	0
 320	1	0.09479761	0.995742738	0.006155041546569217	1
 322	0	-2.16061854	0.0108400183	0.015724220850716938	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-2.48088837	0.00265371148	0.0038335852528692412	0
 408	0	-2.10281515	0.0139513118	0.020269210492385212	0
 410	0	-2.48088837	0.00265371148	0.0038335852528692412	0
-411	0				
+411	0				0
 412	1	-0.0120434761	0.9931908	0.0098571608082237746	0
 417	0	-2.48088837	0.00265371148	0.0038335852528692412	0
 420	0	-1.86625433	0.0386949927	0.056933846240527428	0
diff --git a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt
index 1c905b24c8..105f99fc80 100644
--- a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-SmoothedHinge-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.51313376	0.997060657	0.0042468207167790329	1
 21	1	1.88215756	0.9991858	0.0011751199613487565	1
 22	0	-1.5913856	0.006754517	0.0097777676588594702	0
-23	1				
+23	1				0
 24	0	-1.85515833	0.00270523666	0.0039081201011675363	0
 25	1	0.183981657	0.767693	0.38139863321618261	1
 26	0	-1.596403	0.006638234	0.0096088756803218642	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.48321867	0.244259775	0.40403768061841711	0
 38	1	1.01125383	0.983338952	0.024239302762828055	1
 39	1	-0.0106446743	0.62648654	0.67464458153125895	0
-40	0				
+40	0				0
 41	1	0.8607874	0.9721748	0.040712322202366577	1
 42	1	1.4849956	0.9967589	0.004683544378464086	1
 43	1	-0.7279444	0.121085733	3.0458992041721875	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.404305	0.0128827207	0.018706593545987932	0
 137	0	-1.701774	0.00460771844	0.0066628947272309403	0
 138	0	-1.360993	0.0149499336	0.021731041715098105	0
-139	0				
+139	0				0
 140	0	-1.701774	0.00460771844	0.0066628947272309403	0
 141	0	-1.8888545	0.00240627048	0.0034756978965475691	0
 142	1	0.881847143	0.974092543	0.037869253621396266	1
 143	0	-1.545697	0.007910921	0.01145843020471164	0
 144	0	-1.77846622	0.00353102176	0.0051032026604077695	0
-145	0				
+145	0				0
 146	1	-0.216273546	0.450334132	1.1509322683430081	0
 147	0	-1.82796979	0.00297325244	0.0042958860993499966	0
 148	0	-0.7305672	0.12011648	0.18461554363807445	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.429970026	0.886195242	0.17430351324204957	1
 156	0	-1.92223477	0.0021426254	0.0030944713637373776	0
 157	0	-1.66807771	0.005178785	0.0074908208279084272	0
-158	0				
+158	0				0
 159	1	2.79265332	0.999965847	4.9273870913609948E-05	1
 160	1	2.08471417	0.999597847	0.00058030016510027748	1
 161	0	-1.23200977	0.0232356917	0.033917610773834123	0
 162	0	-1.48099709	0.009891603	0.014341615100451873	0
 163	0	-1.20272636	0.02566766	0.037514142314967996	0
-164	0				
+164	0				0
 165	0	-1.09945023	0.0363804549	0.053464438820388052	0
 166	1	1.35837817	0.99497056	0.0072742561293771086	1
 167	1	1.40636182	0.9957416	0.0061566823680882154	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.0236132145	0.6158536	1.3802718900263455	0
 233	1	1.45269513	0.9963742	0.005240444497289571	1
 234	0	-1.12313449	0.0335955	0.049300920379201259	0
-235	0				
+235	0				0
 236	1	2.801736	0.9999669	4.7725975020197848E-05	1
 237	1	1.18725443	0.9909072	0.013178153095375312	1
 238	1	2.58363461	0.999929249	0.00010207531428030829	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.15890861	0.9996894	0.00044817040124598361	1
 247	1	0.7686317	0.9620387	0.055833170607592193	1
 248	0	-0.9843831	0.0533667132	0.079122441964183776	0
-249	0				
+249	0				0
 250	0	-2.03262329	0.001459477	0.0021071182550953969	0
 251	1	1.98737311	0.999435544	0.0008145677672951316	1
 252	0	0.938287735	0.9786189	5.5475214513768956	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.364958525	0.861275733	0.21545291272160746	1
 273	1	-0.0762293339	0.5716655	0.80675680440858633	0
 274	0	-1.41909039	0.0122437514	0.017773027141160865	0
-275	0				
+275	0				0
 276	0	-1.5913856	0.006754517	0.0097777676588594702	0
 277	0	-1.96554685	0.00184303813	0.0026613952529717312	0
 278	0	-1.85515833	0.00270523666	0.0039081201011675363	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.51208711	0.99705	0.0042622586236973218	1
 290	0	-2.07593513	0.00125529012	0.0018121384446850468	0
 291	0	-1.85515833	0.00270523666	0.0039081201011675363	0
-292	1				
+292	1				0
 293	1	1.33046842	0.9944597	0.0080152036111407286	1
-294	0				
+294	0				0
 295	1	1.2251215	0.9920222	0.011555664783429847	1
 296	0	0.111403227	0.719591737	1.8343992308763424	1
-297	0				
+297	0				0
 298	0	-0.7513188	0.112681925	0.17247673834356275	0
 299	1	1.96303582	0.9993856	0.00088667099785278705	1
 300	1	1.383044	0.995382845	0.0066765713113142704	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.17001605	0.7589018	0.39801492605707506	1
 313	0	-2.07593513	0.00125529012	0.0018121384446850468	0
 314	0	-1.97056413	0.00181115558	0.0026153142649758387	0
-315	0				
+315	0				0
 316	1	0.541802645	0.9199835	0.12032009864475471	1
 317	1	1.56700492	0.9975625	0.0035208219605770688	1
 318	0	-1.84010613	0.00285049225	0.0041182633675105971	0
 319	0	0.05099702	0.675234735	1.6225307564202673	1
 320	1	1.7057507	0.9984955	0.0021721414278146082	1
-321	0				
+321	0				0
 322	0	-1.48099709	0.009891603	0.014341615100451873	0
 323	1	0.7110567	0.95399344	0.067948749601842412	1
 324	0	-1.85515833	0.00270523666	0.0039081201011675363	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-1.45910537	0.0106672905	0.015472318523715401	0
 409	0	-1.54807365	0.007846191	0.011364302031181555	0
 410	0	-1.96554685	0.00184303813	0.0026613952529717312	0
-411	0				
+411	0				0
 412	1	1.61123109	0.9979099	0.0030185274243607983	1
 413	0	-1.063524	0.0410328656	0.060446722723610943	0
 414	1	1.54281878	0.9973487	0.0038300596622238277	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.78348351	0.00347004039	0.0050149160869795298	0
 615	0	-1.31768119	0.0173430257	0.025240206070453266	0
 616	0	-1.5913856	0.006754517	0.0097777676588594702	0
-617	0				
+617	0				0
 618	0	-1.404305	0.0128827207	0.018706593545987932	0
 619	0	-1.21722436	0.024434112	0.035688781701501276	0
 620	0	-1.5913856	0.006754517	0.0097777676588594702	0
diff --git a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-TrainTest-breast-cancer.txt
index ff963fe7a2..d31e2e0f16 100644
--- a/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SDCA/BinarySDCA-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.37743354	0.7985785	0.32449386248842338	1
 21	1	1.7630446	0.853590548	0.22838389385799779	1
 22	0	-1.874893	0.132976577	0.20585712538187464	0
-23	1				
+23	1				0
 24	0	-1.948468	0.124720506	0.19218432401279964	0
 25	1	0.243255854	0.5605158	0.83517300013076445	1
 26	0	-1.79869926	0.142009482	0.22096639052344227	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-1.30918431	0.212623373	0.34487420705553562	0
 38	1	1.52097869	0.8206825	0.28510385981645775	1
 39	1	0.568297148	0.638370156	0.64753488753370236	1
-40	0				
+40	0				0
 41	1	0.08091617	0.520218	0.94281173541226504	1
 42	1	2.4137857	0.9178725	0.12363434755323521	1
 43	1	-0.08661461	0.478359878	1.0638317048217665	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.80893993	0.1407663	0.21887750444885776	0
 137	0	-1.9332242	0.126394138	0.1949455575113978	0
 138	0	-1.70428443	0.153906524	0.24111103479242962	0
-139	0				
+139	0				0
 140	0	-1.9332242	0.126394138	0.1949455575113978	0
 141	0	-1.99917722	0.119289339	0.18325996439997919	0
 142	1	0.6176696	0.649688363	0.62218023037407078	1
 143	0	-1.44733071	0.190412715	0.3047414631100317	0
 144	0	-1.94084609	0.125554934	0.19356034047915699	0
-145	0				
+145	0				0
 146	1	0.272925377	0.567810953	0.81651741701068026	1
 147	0	-1.8198235	0.13945505	0.21667754281184065	0
 148	0	-0.713562	0.328812242	0.57521169167023078	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.9670353	0.7245282	0.46488626460347809	1
 156	0	-1.793424	0.142653435	0.22204959316054371	0
 157	0	-1.882515	0.132100269	0.20439971838260004	0
-158	0				
+158	0				0
 159	1	3.20693851	0.961094558	0.057249715926430703	1
 160	1	2.3220613	0.910687745	0.13497162539860094	1
 161	0	-1.65904641	0.159890041	0.25134992500211428	0
 162	0	-1.81656182	0.139846936	0.21733468482291701	0
 163	0	-1.60762358	0.166918814	0.26347099825296155	0
-164	0				
+164	0				0
 165	0	-1.50459647	0.181740969	0.28937047546414252	0
 166	1	2.457339	0.9210965	0.11857577878171396	1
 167	1	1.31327176	0.7880601	0.34362238392184646	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.213132143	0.446917742	0.85443403273590568	0
 233	1	1.23634028	0.774926364	0.36786886673349695	1
 234	0	-1.00412917	0.268130362	0.4503413991221501	0
-235	0				
+235	0				0
 236	1	2.65734458	0.934462249	0.097791712220334726	1
 237	1	1.59322524	0.8310694	0.26695912082718543	1
 238	1	3.30821967	0.9647097	0.051833223594515407	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	3.32132936	0.965153337	0.051169929428424521	1
 247	1	0.572052956	0.639236748	0.64557774708968529	1
 248	0	-1.29279661	0.215379834	0.34993367973529765	0
-249	0				
+249	0				0
 250	0	-1.85175514	0.135666952	0.21034077001927648	0
 251	1	1.686516	0.843765438	0.24508610192596253	1
 252	0	0.9327009	0.717622936	1.8243051828654713	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.5505221	0.6342567	0.65686119381445462	1
 273	1	-0.451063156	0.389108032	1.3617573340834921	0
 274	0	-1.72499943	0.151228324	0.23655158068052121	0
-275	0				
+275	0				0
 276	0	-1.874893	0.132976577	0.20585712538187464	0
 277	0	-2.00679922	0.1184909	0.18195262731195211	0
 278	0	-1.948468	0.124720506	0.19218432401279964	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	2.363632	0.914011657	0.12971552945936157	1
 290	0	-2.06513023	0.112532459	0.17223374110934919	0
 291	0	-1.948468	0.124720506	0.19218432401279964	0
-292	1				
+292	1				0
 293	1	1.17569327	0.764172554	0.38802965202562639	1
-294	0				
+294	0				0
 295	1	1.9321816	0.8734907	0.1951357665052601	1
 296	0	0.2875533	0.571397066	1.222286369266439	1
-297	0				
+297	0				0
 298	0	-1.39716244	0.198266774	0.31880583096618414	0
 299	1	1.31489539	0.788331151	0.34312631094095036	1
 300	1	1.6675427	0.8412479	0.24939706872810494	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.6733315	0.662248731	0.59455492152164024	1
 313	0	-2.06513023	0.112532459	0.17223374110934919	0
 314	0	-2.03932476	0.115135506	0.17647155325903272	0
-315	0				
+315	0				0
 316	1	0.9730499	0.725726962	0.46250122508222125	1
 317	1	2.53153682	0.9263233	0.11041230078378952	1
 318	0	-1.85089087	0.135768339	0.21051001013383977	0
 319	0	0.279238	0.5693594	1.2154438271457824	1
 320	1	1.35926127	0.795639634	0.32981295026166818	1
-321	0				
+321	0				0
 322	0	-1.81656182	0.139846936	0.21733468482291701	0
 323	1	1.28926969	0.7840235	0.35103115421599534	1
 324	0	-1.948468	0.124720506	0.19218432401279964	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-1.33084726	0.209019259	0.33828552617088203	0
 409	0	-1.77023745	0.1455128	0.22686922143757757	0
 410	0	-2.00679922	0.1184909	0.18195262731195211	0
-411	0				
+411	0				0
 412	1	2.25751042	0.9052964	0.14353790094246915	1
 413	0	-1.58000016	0.170795456	0.27020007178125394	0
 414	1	1.60186315	0.8322786	0.2648615365498318	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.97337174	0.122027189	0.18775183095640005	0
 615	0	-1.59962881	0.1680335	0.26540264924934215	0
 616	0	-1.874893	0.132976577	0.20585712538187464	0
-617	0				
+617	0				0
 618	0	-1.80893993	0.1407663	0.21887750444885776	0
 619	0	-1.74298692	0.148933932	0.23265696296547442	0
 620	0	-1.874893	0.132976577	0.20585712538187464	0
diff --git a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-CV-breast-cancer.txt
index 8b3d215017..f4e8911532 100644
--- a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	0.344691515	0.5853297	0.77267858291118818	1
 35	0	-0.6512495	0.342708021	0.60539371596619707	0
 37	0	-0.503962	0.376610041	0.68179317658398975	0
-40	0				
+40	0				0
 41	1	-0.09442055	0.4764124	1.069717174215209	0
 44	1	0.5798913	0.6410424	0.64150828626867074	1
 45	0	-0.6560674	0.341623574	0.60301541680763648	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-0.597589	0.354895473	0.63239515287919279	0
 141	0	-0.6678773	0.3389723	0.5972173671855312	0
 144	0	-0.6512495	0.342708021	0.60539371596619707	0
-145	0				
+145	0				0
 147	0	-0.6018609	0.353918076	0.63021098184538349	0
 150	0	-0.656989932	0.3414161	0.60256083089734203	0
 151	1	0.160812974	0.540116847	0.88865654739065503	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-0.67789495	0.336731285	0.59233461600767046	0
 156	0	-0.5912131	0.356356561	0.63566639957530646	0
 161	0	-0.5840918	0.3579916	0.63933593475596628	0
-164	0				
+164	0				0
 167	1	0.315922141	0.5783301	0.79003490476906479	1
 169	0	-0.6661818	0.33935234	0.59804704249396301	0
 171	0	-0.644639254	0.344198585	0.60866907932442826	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	0.9649427	0.7241103	0.46571861194179465	1
 247	1	0.07307994	0.51826185	0.94824689644610127	1
 248	0	-0.4621131	0.386484653	0.70482866116462817	0
-249	0				
+249	0				0
 250	0	-0.607840955	0.352551848	0.62716342858897578	0
 252	0	0.210040927	0.552318037	1.1594538998856256	1
 254	1	0.5551709	0.635334432	0.65441188637353787	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-0.644639254	0.344198585	0.60866907932442826	0
 271	0	-0.6045689	0.3532991	0.62882950155653372	0
 272	1	0.109180689	0.5272681	0.92339134731632821	1
-275	0				
+275	0				0
 276	0	-0.6412319	0.3449681	0.61036295013192154	0
 277	0	-0.6612671	0.340455025	0.60045705425766605	0
 278	0	-0.644639254	0.344198585	0.60866907932442826	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-0.644639254	0.344198585	0.60866907932442826	0
 293	1	0.2438618	0.560665131	0.83478874766701627	1
 296	0	0.0298114419	0.5074523	1.0216646747888918	1
-297	0				
+297	0				0
 299	1	0.29232645	0.5725656	0.80448706147450022	1
 300	1	0.440484524	0.6083745	0.71696846696669991	1
 301	0	-0.644639254	0.344198585	0.60866907932442826	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.23788023	0.5591912	0.83858636815416177	1
 317	1	0.736536	0.676237941	0.56439713300164063	1
 319	0	0.032892406	0.508222342	1.0239219003304794	1
-321	0				
+321	0				0
 323	1	0.3295461	0.581648946	0.78177941761076775	1
 327	0	-0.6612671	0.340455025	0.60045705425766605	0
 328	1	0.309677362	0.5768065	0.79384070845234189	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	1.18309152	0.7655032	0.38551963408922602	1
 613	0	-0.578392267	0.3593026	0.64228498181768678	0
 614	0	-0.663600147	0.339931339	0.59931199209014285	0
-617	0				
+617	0				0
 618	0	-0.6312144	0.347235233	0.61536490408676614	0
 619	0	-0.621196747	0.349509329	0.62039972730149728	0
 621	0	-0.2970261	0.426284641	0.80159295389429652	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-0.5587295	0.363841474	0.65254177576954708	0
 19	0	-0.521061659	0.372604	0.67255179238253271	0
 22	0	-0.597002566	0.355029762	0.63269550517202178	0
-23	1				
+23	1				0
 24	0	-0.6152313	0.3508668	0.62341353797116505	0
 26	0	-0.568058968	0.361684829	0.64765915777643768	0
 27	0	-0.559334755	0.3637014	0.6522241546694586	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-0.586384356	0.35746488	0.6381527823333405	0
 135	0	-0.4233432	0.395717025	0.72670379813371644	0
 136	0	-0.578168631	0.3593541	0.6424009484072789	0
-139	0				
+139	0				0
 140	0	-0.6164417	0.350591153	0.62280105585760936	0
 142	1	0.253997982	0.5631603	0.82838245949919198	1
 143	0	-0.455442041	0.388067663	0.70855595514156899	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-0.498274028	0.377946377	0.68488914380895782	0
 155	1	0.381782949	0.5943031	0.75072925773026189	1
 157	0	-0.5963973	0.355168372	0.63300558819075581	0
-158	0				
+158	0				0
 159	1	1.14907432	0.7593418	0.3971787124185161	1
 160	1	0.835970342	0.697615862	0.51949525142708575	1
 162	0	-0.5775634	0.359493434	0.64271473576785443	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	0.867232	0.7041694	0.50600557448041072	1
 232	0	-0.0153304338	0.496167481	0.98898385339386186	0
 234	0	-0.28234	0.4298802	0.81066299300396294	0
-235	0				
+235	0				0
 236	1	0.9360302	0.718297064	0.47734747567952907	1
 238	1	1.21385264	0.770979941	0.37523476983545384	1
 243	0	-0.3776855	0.406685263	0.7531304771823496	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	1.42419529	0.8059953	0.31115669483110281	1
 287	0	-0.586384356	0.35746488	0.6381527823333405	0
 289	1	0.8870376	0.7082785	0.49761139182067243	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	0.7293541	0.674663544	0.56775988879752004	1
 298	0	-0.4508557	0.389157325	0.711127239010238	0
 302	1	1.38025045	0.7990312	0.3236762608744207	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-0.6152313	0.3508668	0.62341353797116505	0
 310	0	-0.6052183	0.353150755	0.62849857907527806	0
 313	0	-0.654109538	0.342064053	0.60398095649539585	0
-315	0				
+315	0				0
 318	0	-0.5833766	0.358156025	0.63970545866432549	0
 320	1	0.483023465	0.618461549	0.69324419149565364	1
 322	0	-0.5775634	0.359493434	0.64271473576785443	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-0.6346704	0.3464523	0.61363554879852178	0
 408	0	-0.398791075	0.401602834	0.74082475334425091	0
 410	0	-0.6346704	0.3464523	0.61363554879852178	0
-411	0				
+411	0				0
 412	1	0.851157367	0.7008099	0.51290494780474771	1
 417	0	-0.6346704	0.3464523	0.61363554879852178	0
 420	0	-0.3393041	0.415978521	0.77590666598714197	0
diff --git a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-CV-breast-cancer.txt
index a2364522f6..a2bfaeeb70 100644
--- a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	0.6522908	0.9885379	0.01663180464505477	1
 35	0	-1.12420082	0.0107460516	0.015587176400536187	0
 37	0	-0.865502357	0.0386134759	0.056811513682664551	0
-40	0				
+40	0				0
 41	1	-0.1372056	0.6145622	0.70236902985400396	0
 44	1	1.0547893	0.9984863	0.0021854902279334833	1
 45	0	-1.13070083	0.0104023358	0.015085999817509936	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-1.03150129	0.0170594156	0.024823881934527593	0
 141	0	-1.15380061	0.00926659	0.0134311903289673	0
 144	0	-1.12420082	0.0107460516	0.015587176400536187	0
-145	0				
+145	0				0
 147	0	-1.03270125	0.0169580057	0.024675046951938132	0
 150	0	-1.13440084	0.0102115627	0.0148079061901775	0
 151	1	0.335192084	0.945543051	0.080784949020458824	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-1.17080045	0.008510069	0.012329973523626827	0
 156	0	-1.01700115	0.0183329377	0.026694285275120175	0
 161	0	-1.00710154	0.0192555338	0.028050804915513337	0
-164	0				
+164	0				0
 167	1	0.6017914	0.98525393	0.021432495728287648	1
 169	0	-1.15050054	0.009420992	0.013656046492446974	0
 171	0	-1.11160088	0.01144463	0.016606319988959024	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	1.7594862	0.999956965	6.208707291578748E-05	1
 247	1	0.172593474	0.8841638	0.17761443218515088	1
 248	0	-0.793102443	0.0547425	0.081220704071742325	0
-249	0				
+249	0				0
 250	0	-1.04660094	0.0158256628	0.0230141968119793	0
 252	0	0.423291922	0.964417338	4.8126817596940885	1
 254	1	1.03148985	0.998297453	0.0024583495418655562	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-1.11160088	0.01144463	0.016606319988959024	0
 271	0	-1.04360127	0.01606356	0.023362970756245272	0
 272	1	0.243792772	0.9162424	0.12619873583154692	1
-275	0				
+275	0				0
 276	0	-1.10720086	0.0116990069	0.016977604564195337	0
 277	0	-1.14120078	0.009869945	0.014310057532988397	0
 278	0	-1.11160088	0.01144463	0.016606319988959024	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-1.11160088	0.01144463	0.016606319988959024	0
 293	1	0.478191853	0.97280544	0.039776797794310127	1
 296	0	0.0886935	0.83318603	2.5836879844847194	1
-297	0				
+297	0				0
 299	1	0.5653906	0.9823277	0.025723714124946184	1
 300	1	0.8071904	0.994728446	0.0076253612609159995	1
 301	0	-1.11160088	0.01144463	0.016606319988959024	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	0.472591877	0.9720465	0.040902773075660377	1
 317	1	1.35288787	0.9996641	0.00048464251232972397	1
 319	0	0.100693226	0.841446757	2.6569607115771978	1
-321	0				
+321	0				0
 323	1	0.6351912	0.987516046	0.018123905012295945	1
 327	0	-1.14120078	0.009869945	0.014310057532988397	0
 328	1	0.5871916	0.9841424	0.023060980928491851	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	2.158784	0.9999943	8.2551908597278378E-06	1
 613	0	-0.993201256	0.0206282046	0.030071445887912274	0
 614	0	-1.14700067	0.009587526	0.013898610301947204	0
-617	0				
+617	0				0
 618	0	-1.090201	0.0127353743	0.018491259389232038	0
 619	0	-1.07320118	0.0138622615	0.020138926273650697	0
 621	0	-0.4947039	0.207426473	0.33538331559891793	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-1.02980137	0.0147205992	0.021395199721883466	0
 19	0	-0.9630018	0.0192868058	0.028096807322037363	0
 22	0	-1.0968008	0.011213962	0.016269722836470393	0
-23	1				
+23	1				0
 24	0	-1.13000059	0.00979631	0.014202769680513335	0
 26	0	-1.04700089	0.0137287723	0.019943648017493942	0
 27	0	-1.03000128	0.0147086745	0.021377739156459911	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-1.079601	0.0120263351	0.017455508586451673	0
 135	0	-0.7955023	0.03769685	0.055436642942084668	0
 136	0	-1.0634011	0.0128445318	0.018650780679196597	0
-139	0				
+139	0				0
 140	0	-1.13040054	0.009780362	0.014179534189705549	0
 142	1	0.3573923	0.8180728	0.2896988683892544	1
 143	0	-0.8376017	0.03189309	0.046761717990888088	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-0.917201638	0.0231931154	0.033854726268903304	0
 155	1	0.5948919	0.922758937	0.1159742899072022	1
 157	0	-1.09660089	0.0112230852	0.016283034217764617	0
-158	0				
+158	0				0
 159	1	1.88818586	0.9995909	0.00059036523296398255	1
 160	1	1.36718786	0.996521652	0.0050269435856363917	1
 162	0	-1.06320107	0.01285497	0.018666035936317264	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1.39838827	0.9969394	0.0044222533640880836	1
 232	0	-0.118705273	0.38808772	0.70860324232262772	0
 234	0	-0.57100296	0.08979461	0.13573597071280369	0
-235	0				
+235	0				0
 236	1	1.52918732	0.9982108	0.0025835996006501579	1
 238	1	1.96808636	0.9997055	0.00042494571667690465	1
 243	0	-0.703202665	0.0541654155	0.080340199841784268	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	2.32438421	0.999932	9.8119438852589428E-05	1
 287	0	-1.079601	0.0120263351	0.017455508586451673	0
 289	1	1.42798841	0.99728936	0.0039159372565436843	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	1.171589	0.9922556	0.011216254621805593	1
 298	0	-0.8448025	0.0309909787	0.045417997957015462	0
 302	1	2.26218414	0.999912143	0.00012675678201834402	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-1.13000059	0.00979631	0.014202769680513335	0
 310	0	-1.11300075	0.0104985284	0.015226241971828952	0
 313	0	-1.19720018	0.007447739	0.010785028389452023	0
-315	0				
+315	0				0
 318	0	-1.07840109	0.0120851332	0.017541371482030246	0
 320	1	0.77709043	0.961948335	0.055968683838555341	1
 322	0	-1.06320107	0.01285497	0.018666035936317264	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-1.16360033	0.008542378	0.012376987044267063	0
 408	0	-0.7606021	0.0432654768	0.063809436873055653	0
 410	0	-1.16360033	0.008542378	0.012376987044267063	0
-411	0				
+411	0				0
 412	1	1.35098827	0.9962829	0.0053726686646499901	1
 417	0	-1.16360033	0.008542378	0.012376987044267063	0
 420	0	-0.6557027	0.0650944263	0.097107435980156739	0
diff --git a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt
index 9dec61f554..deb3abc49a 100644
--- a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-Hinge-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	1.222367	0.9828292	0.024987354577091989	1
 21	1	1.49796534	0.9935609	0.0093196803205346252	1
 22	0	-1.19740391	0.009379565	0.013595712679399167	0
-23	1				
+23	1				0
 24	0	-1.23810339	0.008112156	0.01175109505221196	0
 25	1	0.3802781	0.7344174	0.4453278964846259	1
 26	0	-1.14100432	0.01146578	0.016637187062001499	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.79460907	0.0387752019	0.057054226638771945	0
 38	1	1.34886718	0.989039242	0.015900330726329494	1
 39	1	0.6641748	0.8848001	0.17657658460400094	1
-40	0				
+40	0				0
 41	1	0.223279715	0.611168444	0.7103580388075188	1
 42	1	2.04505968	0.999095738	0.0013051645925104319	1
 43	1	0.169680834	0.56447953	0.82500683046719547	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-1.15510464	0.0109047387	0.015818618982627604	0
 137	0	-1.24130344	0.008020028	0.011617101215948859	0
 138	0	-1.0749054	0.0144998142	0.021071951694510416	0
-139	0				
+139	0				0
 140	0	-1.24130344	0.008020028	0.011617101215948859	0
 141	0	-1.28360271	0.00689550675	0.0099825705316781733	0
 142	1	0.643275	0.8769101	0.18949916409473391	1
 143	0	-0.8591082	0.0309929028	0.04542086264678518	0
 144	0	-1.23970342	0.008065961	0.011683906942824285	0
-145	0				
+145	0				0
 146	1	0.4436772	0.7764816	0.36497630408526505	1
 147	0	-1.13820457	0.01158053	0.016804665017851262	0
 148	0	-0.320714116	0.181648508	0.2892074628941344	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.9467714	0.9550218	0.066394431489110783	1
 156	0	-1.11830425	0.0124295028	0.018044356997620709	0
 157	0	-1.19580388	0.009433212	0.013673843835136703	0
-158	0				
+158	0				0
 159	1	2.5887537	0.9998721	0.0001845491876153846	1
 160	1	1.92586017	0.9986121	0.0020036987954509607	1
 161	0	-1.04420578	0.01616599	0.023513167231551696	0
 162	0	-1.15350461	0.0109670116	0.015909453114236246	0
 163	0	-1.00530624	0.0185497329	0.027012930786301039	0
-164	0				
+164	0				0
 165	0	-0.9275073	0.0243961066	0.035632579294711073	0
 166	1	2.06175947	0.9991484	0.0012290814661556479	1
 167	1	1.15397048	0.9781426	0.031883260676163518	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	0.0278829336	0.437610149	0.83035753638984611	1
 233	1	1.11616874	0.975037336	0.036470630963644925	1
 234	0	-0.544210553	0.09034561	0.13660958234622511	0
-235	0				
+235	0				0
 236	1	2.15735817	0.999396145	0.00087144125636392123	1
 237	1	1.37376881	0.9899692	0.014544463077068375	1
 238	1	2.659554	0.9999008	0.00014309666195095306	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	2.70435286	0.9999156	0.00012176885553963592	1
 247	1	0.616675138	0.8662006	0.207226880023576	1
 248	0	-0.7762085	0.04131975	0.060878383940094143	0
-249	0				
+249	0				0
 250	0	-1.16220379	0.0106326314	0.015421777653289784	0
 251	1	1.43526506	0.9919444	0.011668877043853167	1
 252	0	0.8921714	0.9457866	4.2052065773298537	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.6439743	0.8771814	0.18905285611569214	1
 273	1	-0.149016142	0.29164663	1.7777066932129042	0
 274	0	-1.08650517	0.0139153069	0.020216532376881539	0
-275	0				
+275	0				0
 276	0	-1.19740391	0.009379565	0.013595712679399167	0
 277	0	-1.28200269	0.00693504466	0.010040008870103924	0
 278	0	-1.23810339	0.008112156	0.01175109505221196	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.98086047	0.998861	0.0016441447437435472	1
 290	0	-1.32590222	0.005927712	0.0085773281383116576	0
 291	0	-1.23810339	0.008112156	0.01175109505221196	0
-292	1				
+292	1				0
 293	1	1.05756974	0.9693573	0.044899543967322132	1
-294	0				
+294	0				0
 295	1	1.67846322	0.9966264	0.0048753374261991068	1
 296	0	0.418977976	0.760678768	2.062979700875831	1
-297	0				
+297	0				0
 298	0	-0.865008354	0.0303616133	0.044481280497859745	0
 299	1	1.15566754	0.9782728	0.031691271742118471	1
 300	1	1.43996739	0.9920784	0.011473925159666753	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.7111747	0.9009488	0.15048293737780147	1
 313	0	-1.32590222	0.005927712	0.0085773281383116576	0
 314	0	-1.3091023	0.006294775	0.0091101437491470354	0
-315	0				
+315	0				0
 316	1	0.9520712	0.955833852	0.065168231187009498	1
 317	1	2.1167593	0.999301255	0.0010084286664473847	1
 318	0	-1.15680456	0.0108389612	0.015722679136914018	0
 319	0	0.43477726	0.7708744	2.1257893169799549	1
 320	1	1.20646763	0.9818366	0.026445122755562926	1
-321	0				
+321	0				0
 322	0	-1.15350461	0.0109670116	0.015909453114236246	0
 323	1	1.1870687	0.980549	0.028338400890888689	1
 324	0	-1.23810339	0.008112156	0.01175109505221196	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-0.775208354	0.0414625444	0.061093287384022553	0
 409	0	-1.11720467	0.0124781644	0.018115446186086449	0
 410	0	-1.28200269	0.00693504466	0.010040008870103924	0
-411	0				
+411	0				0
 412	1	1.89956212	0.9984746	0.0022023701778286324	1
 413	0	-0.9887064	0.01966903	0.028659194266170487	0
 414	1	1.3937664	0.9906591	0.013539378350893604	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.266803	0.00732205063	0.010602349145536318	0
 615	0	-0.994706035	0.0192570463	0.028053029788189736	0
 616	0	-1.19740391	0.009379565	0.013595712679399167	0
-617	0				
+617	0				0
 618	0	-1.15510464	0.0109047387	0.015818618982627604	0
 619	0	-1.11280513	0.0126747517	0.018402674010350579	0
 620	0	-1.19740391	0.009379565	0.013595712679399167	0
diff --git a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-TrainTest-breast-cancer.txt
index 29a93c0326..3f80a3624c 100644
--- a/test/BaselineOutput/SingleRelease/SGD/BinarySGD-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SGD/BinarySGD-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	0.822916269	0.694855034	0.52521607106152413	1
 21	1	1.02655149	0.736246765	0.441738705665011	1
 22	0	-1.01600647	0.265806019	0.44576680836978433	0
-23	1				
+23	1				0
 24	0	-1.03864312	0.261411875	0.43715802871945769	0
 25	1	0.184996247	0.5461176	0.87271643290195555	1
 26	0	-0.9708479	0.274711519	0.46337315957197994	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-0.7265403	0.325954378	0.56908185228017971	0
 38	1	0.933466434	0.717778	0.47839033548395937	1
 39	1	0.4073757	0.600458443	0.7358636922780708	1
-40	0				
+40	0				0
 41	1	0.04465425	0.5111617	0.96814839425710286	1
 42	1	1.43612671	0.8078541	0.30783330336923359	1
 43	1	0.0479370356	0.511981964	0.96583510643055481	1
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-0.9885073	0.271207035	0.45641906112335939	0
 137	0	-1.04836845	0.259538531	0.4335034307664255	0
 138	0	-0.9260764	0.283721417	0.48140728969854896	0
-139	0				
+139	0				0
 140	0	-1.04836845	0.259538531	0.4335034307664255	0
 141	0	-1.07586777	0.2542888	0.42331107075059288	0
 142	1	0.373193622	0.592230439	0.75576945149404562	1
 143	0	-0.7654944	0.317454576	0.55100303407297502	0
 144	0	-1.04350591	0.2604741	0.43532739229387868	0
-145	0				
+145	0				0
 146	1	0.2147963	0.553493559	0.85336156547352904	1
 147	0	-0.9662212	0.275634348	0.46520995753133637	0
 148	0	-0.318193555	0.421116054	0.78865394770237895	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	0.600466	0.6457629	0.63092349091318589	1
 156	0	-0.9430999	0.2802746	0.47448152072334643	0
 157	0	-1.01114392	0.266756058	0.44763484776839352	0
-158	0				
+158	0				0
 159	1	1.87013483	0.866473854	0.20677187910596315	1
 160	1	1.34225249	0.7928601	0.33486178660539723	1
 161	0	-0.901281357	0.288787246	0.49164689849299364	0
 162	0	-0.9836446	0.2721692	0.45832499621527728	0
 163	0	-0.855002642	0.2983845	0.51124744948014056	0
-164	0				
+164	0				0
 165	0	-0.8168132	0.306440562	0.5279085681868505	0
 166	1	1.49839211	0.817334533	0.29100140459599977	1
 167	1	0.8153703	0.6932527	0.5285468008024331	1
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-0.08038044	0.4799157	0.9431826305616432	0
 233	1	0.6980891	0.667763948	0.58258988829378422	1
 234	0	-0.49562943	0.378568321	0.68633230772699549	0
-235	0				
+235	0				0
 236	1	1.52862382	0.8218049	0.28313219549408758	1
 237	1	0.9843018	0.727960944	0.45806704440223556	1
 238	1	1.96605682	0.877186954	0.18904373922390869	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	1.97140193	0.8777616	0.18809893386755816	1
 247	1	0.323040724	0.580065131	0.78571319608569612	1
 248	0	-0.6818254	0.335854024	0.59042772056631165	0
-249	0				
+249	0				0
 250	0	-0.9754619	0.273793161	0.46154757804170599	0
 251	1	0.9712138	0.725361347	0.46322822535916075	1
 252	0	0.5616691	0.6368387	1.4613175226151991	1
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	0.354397058	0.587683439	0.76688885070680657	1
 273	1	-0.237432361	0.4409192	1.1814138244518058	0
 274	0	-0.9287806	0.28317216	0.48030142611403009	0
-275	0				
+275	0				0
 276	0	-1.01600647	0.265806019	0.44576680836978433	0
 277	0	-1.07100511	0.255211979	0.42509822607281988	0
 278	0	-1.03864312	0.261411875	0.43715802871945769	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	1.4364171	0.8078992	0.30775283385408775	1
 290	0	-1.10336709	0.249109536	0.4133256254437066	0
 291	0	-1.03864312	0.261411875	0.43715802871945769	0
-292	1				
+292	1				0
 293	1	0.6671076	0.6608552	0.59759395409472371	1
-294	0				
+294	0				0
 295	1	1.17509961	0.764065564	0.38823165513968877	1
 296	0	0.224430084	0.5558732	1.1709565135958244	1
-297	0				
+297	0				0
 298	0	-0.7844506	0.313361466	0.54237727145415437	0
 299	1	0.748945951	0.678949	0.55862488926125509	1
 300	1	1.01898217	0.7347743	0.44462694496525584	1
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	0.4770298	0.617046237	0.69654949630747753	1
 313	0	-1.10336709	0.249109536	0.4133256254437066	0
 314	0	-1.09132075	0.251369655	0.41767456748452503	0
-315	0				
+315	0				0
 316	1	0.5936177	0.6441948	0.63443112049115613	1
 317	1	1.53676748	0.8229943	0.28104567061447505	1
 318	0	-0.977696	0.2733492	0.46066585861057346	0
 319	0	0.228058934	0.5567689	1.1738689621124481	1
 320	1	0.7848048	0.6867147	0.54221722972478248	1
-321	0				
+321	0				0
 322	0	-0.9836446	0.2721692	0.45832499621527728	0
 323	1	0.799038649	0.6897688	0.53581523979313106	1
 324	0	-1.03864312	0.261411875	0.43715802871945769	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-0.6859037	0.334944934	0.58845429463916576	0
 409	0	-0.9535757	0.2781663	0.47026158367983178	0
 410	0	-1.07100511	0.255211979	0.42509822607281988	0
-411	0				
+411	0				0
 412	1	1.353524	0.794705153	0.331508396641091	1
 413	0	-0.8662151	0.296042472	0.50643970604072797	0
 414	1	0.9272311	0.7165132	0.48093477882048502	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-1.06382155	0.256579816	0.42775023737254403	0
 615	0	-0.863645554	0.296578258	0.50753816766843873	0
 616	0	-1.01600647	0.265806019	0.44576680836978433	0
-617	0				
+617	0				0
 618	0	-0.9885073	0.271207035	0.45641906112335939	0
 619	0	-0.961007953	0.276676446	0.46728696355201749	0
 620	0	-1.01600647	0.265806019	0.44576680836978433	0
diff --git a/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-CV-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-CV-breast-cancer.txt
index d0e7499c6d..5218dcbd4f 100644
--- a/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-CV-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-CV-breast-cancer.txt
@@ -14,7 +14,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 32	1	454.251282	1	0	1
 35	0	-320.737427	0	0	0
 37	0	-78.9787	5.011722E-35	0	0
-40	0				
+40	0				0
 41	1	199.0091	1	0	1
 44	1	656.8247	1	0	1
 45	0	-322.804565	0	0	0
@@ -76,7 +76,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 138	0	-289.415222	0	0	0
 141	0	-344.61084	0	0	0
 144	0	-320.737427	0	0	0
-145	0				
+145	0				0
 147	0	-309.023651	0	0	0
 150	0	-272.79837	0	0	0
 151	1	249.55658	1	0	1
@@ -84,7 +84,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 154	0	-349.126221	0	0	0
 156	0	-227.212433	0	0	0
 161	0	-274.6302	0	0	0
-164	0				
+164	0				0
 167	1	283.316284	1	0	1
 169	0	-331.047241	0	0	0
 171	0	-301.379425	0	0	0
@@ -130,7 +130,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	1044.54126	1	0	1
 247	1	409.237671	1	0	1
 248	0	-221.818024	0	0	0
-249	0				
+249	0				0
 250	0	-251.085815	0	0	0
 252	0	307.68988	1	Infinity	1
 254	1	728.536743	1	0	1
@@ -144,7 +144,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 269	0	-301.379425	0	0	0
 271	0	-283.3178	0	0	0
 272	1	408.017578	1	0	1
-275	0				
+275	0				0
 276	0	-316.222015	0	0	0
 277	0	-325.252838	0	0	0
 278	0	-301.379425	0	0	0
@@ -158,7 +158,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 291	0	-301.379425	0	0	0
 293	1	386.6949	1	0	1
 296	0	139.220642	1	Infinity	1
-297	0				
+297	0				0
 299	1	227.814941	1	0	1
 300	1	407.6792	1	0	1
 301	0	-301.379425	0	0	0
@@ -172,7 +172,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 316	1	466.170166	1	0	1
 317	1	736.0132	1	0	1
 319	0	161.598083	1	Infinity	1
-321	0				
+321	0				0
 323	1	388.03302	1	0	1
 327	0	-325.252838	0	0	0
 328	1	584.984	1	0	1
@@ -318,7 +318,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 612	1	1115.01685	1	0	1
 613	0	-169.23941	0	0	0
 614	0	-292.156342	0	0	0
-617	0				
+617	0				0
 618	0	-311.7066	0	0	0
 619	0	-307.1912	0	0	0
 621	0	-15.8763733	1.27344038E-07	1.8371862313930792E-07	0
@@ -375,7 +375,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 17	0	-643.057739	0	0	0
 19	0	-668.631836	0	0	0
 22	0	-540.900146	0	0	0
-23	1				
+23	1				0
 24	0	-604.696655	0	0	0
 26	0	-270.657074	0	0	0
 27	0	-566.4742	0	0	0
@@ -425,7 +425,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 134	0	-670.7141	0	0	0
 135	0	-421.652374	0	0	0
 136	0	-553.6872	0	0	0
-139	0				
+139	0				0
 140	0	-451.529541	0	0	0
 142	1	488.315338	1	0	1
 143	0	-142.331116	0	0	0
@@ -435,7 +435,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 153	0	-322.504425	0	0	0
 155	1	1089.60254	1	0	1
 157	0	-617.483643	0	0	0
-158	0				
+158	0				0
 159	1	1923.50525	1	0	1
 160	1	1494.5094	1	0	1
 162	0	-630.2707	0	0	0
@@ -474,7 +474,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 231	1	1347.16248	1	0	1
 232	0	355.92923	1	Infinity	1
 234	0	50.92752	1	Infinity	1
-235	0				
+235	0				0
 236	1	1204.77161	1	0	1
 238	1	2421.62354	1	0	1
 243	0	-499.813416	0	0	0
@@ -496,8 +496,8 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 286	1	1933.38391	1	0	1
 287	0	-670.7141	0	0	0
 289	1	1586.01746	1	0	1
-292	1				
-294	0				
+292	1				0
+294	0				0
 295	1	906.5393	1	0	1
 298	0	-764.4775	0	0	0
 302	1	1682.504	1	0	1
@@ -506,7 +506,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 307	0	-604.696655	0	0	0
 310	0	-657.927	0	0	0
 313	0	-425.9555	0	0	0
-315	0				
+315	0				0
 318	0	-994.1385	0	0	0
 320	1	276.6519	1	0	1
 322	0	-630.2707	0	0	0
@@ -551,7 +551,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 407	0	-515.32605	0	0	0
 408	0	-106.253662	0	0	0
 410	0	-515.32605	0	0	0
-411	0				
+411	0				0
 412	1	1142.7179	1	0	1
 417	0	-515.32605	0	0	0
 420	0	-151.036346	0	0	0
diff --git a/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-TrainTest-breast-cancer.txt b/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-TrainTest-breast-cancer.txt
index f744bc3525..64a3a40edd 100644
--- a/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-TrainTest-breast-cancer.txt
+++ b/test/BaselineOutput/SingleRelease/SymSGD/SymSGD-TrainTest-breast-cancer.txt
@@ -22,7 +22,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 20	1	10.1497192	0.9999609	5.6411412351548271E-05	1
 21	1	-61.521698	1.91190378E-27	88.757048641689195	0
 22	0	-407.94165	0	0	0
-23	1				
+23	1				0
 24	0	-413.829132	0	0	0
 25	1	-111.690765	0	Infinity	0
 26	0	-333.49762	0	0	0
@@ -39,7 +39,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 37	0	-367.9438	0	0	0
 38	1	125.049805	1	0	1
 39	1	-120.420319	0	Infinity	0
-40	0				
+40	0				0
 41	1	-214.114883	0	Infinity	0
 42	1	86.67383	1	0	1
 43	1	-299.954132	0	Infinity	0
@@ -138,13 +138,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 136	0	-408.326935	0	0	0
 137	0	-401.2836	0	0	0
 138	0	-411.7511	0	0	0
-139	0				
+139	0				0
 140	0	-401.2836	0	0	0
 141	0	-400.898315	0	0	0
 142	1	-108.134125	0	Infinity	0
 143	0	-305.7808	0	0	0
 144	0	-407.556366	0	0	0
-145	0				
+145	0				0
 146	1	-205.1228	0	Infinity	0
 147	0	-408.638123	0	0	0
 148	0	-448.917847	0	0	0
@@ -157,13 +157,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 155	1	39.9500122	1	0	1
 156	0	-361.30127	0	0	0
 157	0	-414.214417	0	0	0
-158	0				
+158	0				0
 159	1	214.183228	1	0	1
 160	1	120.047485	1	0	1
 161	0	-401.219147	0	0	0
 162	0	-414.5997	0	0	0
 163	0	-282.1694	0	0	0
-164	0				
+164	0				0
 165	0	-377.536072	0	0	0
 166	1	123.761658	1	0	1
 167	1	-9.15014648	0.000106192965	13.201024182527696	0
@@ -234,7 +234,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 232	0	-256.504028	0	0	0
 233	1	-84.9973755	1.21929513E-37	122.62529213957316	0
 234	0	-275.7568	0	0	0
-235	0				
+235	0				0
 236	1	116.098267	1	0	1
 237	1	26.0986938	1	0	1
 238	1	370.027954	1	0	1
@@ -248,7 +248,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 246	1	321.109131	1	0	1
 247	1	-61.9207153	1.28284749E-27	89.332708892981643	0
 248	0	-346.1557	0	0	0
-249	0				
+249	0				0
 250	0	-354.643219	0	0	0
 251	1	108.2807	1	0	1
 252	0	-4.193939	0.0148625113	0.021603009492489122	0
@@ -274,7 +274,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 272	1	-151.574524	0	Infinity	0
 273	1	-303.688629	0	Infinity	0
 274	0	-400.833862	0	0	0
-275	0				
+275	0				0
 276	0	-407.94165	0	0	0
 277	0	-407.171082	0	0	0
 278	0	-413.829132	0	0	0
@@ -291,12 +291,12 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 289	1	175.671082	1	0	1
 290	0	-400.513	0	0	0
 291	0	-413.829132	0	0	0
-292	1				
+292	1				0
 293	1	51.4936523	1	0	1
-294	0				
+294	0				0
 295	1	5.8543396	0.997140765	0.0041309123233919023	1
 296	0	-173.148254	0	0	0
-297	0				
+297	0				0
 298	0	-429.3664	0	0	0
 299	1	-112.8385	0	Infinity	0
 300	1	-114.377228	0	Infinity	0
@@ -314,13 +314,13 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 312	1	-175.547363	0	Infinity	0
 313	0	-400.513	0	0	0
 314	0	-382.020966	0	0	0
-315	0				
+315	0				0
 316	1	-56.5515747	2.753995E-25	81.586676422594735	0
 317	1	168.155884	1	0	1
 318	0	-489.2794	0	0	0
 319	0	-232.038055	0	0	0
 320	1	16.8273315	0.99999994	8.5991327994145617E-08	1
-321	0				
+321	0				0
 322	0	-414.5997	0	0	0
 323	1	72.79901	1	0	1
 324	0	-413.829132	0	0	0
@@ -410,7 +410,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 408	0	-278.598877	0	0	0
 409	0	-411.365784	0	0	0
 410	0	-407.171082	0	0	0
-411	0				
+411	0				0
 412	1	21.296814	1	0	1
 413	0	-418.794434	0	0	0
 414	1	17.1500549	0.99999994	8.5991327994145617E-08	1
@@ -616,7 +616,7 @@ Instance	Label	Score	Probability	Log-loss	Assigned
 614	0	-382.40625	0	0	0
 615	0	-415.175232	0	0	0
 616	0	-407.94165	0	0	0
-617	0				
+617	0				0
 618	0	-408.326935	0	0	0
 619	0	-408.712219	0	0	0
 620	0	-407.94165	0	0	0
diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs b/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs
index 35859783ad..124dd338a2 100644
--- a/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs
+++ b/test/Microsoft.ML.Core.Tests/UnitTests/CoreBaseTestClass.cs
@@ -178,7 +178,7 @@ protected Func<bool> GetColumnComparer(IRow r1, IRow r2, int col, ColumnType typ
                     case DataKind.Text:
                         return GetComparerOne<DvText>(r1, r2, col, DvText.Identical);
                     case DataKind.Bool:
-                        return GetComparerOne<DvBool>(r1, r2, col, (x, y) => x.Equals(y));
+                        return GetComparerOne<bool>(r1, r2, col, (x, y) => x == y);
                     case DataKind.TimeSpan:
                         return GetComparerOne<DvTimeSpan>(r1, r2, col, (x, y) => x.Equals(y));
                     case DataKind.DT:
@@ -221,7 +221,7 @@ protected Func<bool> GetColumnComparer(IRow r1, IRow r2, int col, ColumnType typ
                     case DataKind.Text:
                         return GetComparerVec<DvText>(r1, r2, col, size, DvText.Identical);
                     case DataKind.Bool:
-                        return GetComparerVec<DvBool>(r1, r2, col, size, (x, y) => x.Equals(y));
+                        return GetComparerVec<bool>(r1, r2, col, size, (x, y) => x == y);
                     case DataKind.TimeSpan:
                         return GetComparerVec<DvTimeSpan>(r1, r2, col, size, (x, y) => x.Equals(y));
                     case DataKind.DT:
diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs b/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs
index a3f5d8231b..ed71fa97f5 100644
--- a/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs
+++ b/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs
@@ -10,60 +10,6 @@ namespace Microsoft.ML.Runtime.RunTests
 {
     public sealed class DvTypeTests
     {
-        [Fact]
-        public void TestComparableDvInt4()
-        {
-            const int count = 100;
-
-            var rand = RandomUtils.Create(42);
-            var values = new DvInt4[2 * count];
-            for (int i = 0; i < count; i++)
-            {
-                var v = values[i] = rand.Next();
-                values[values.Length - i - 1] = v;
-            }
-
-            // Assign two NA's at random.
-            int iv1 = rand.Next(values.Length);
-            int iv2 = rand.Next(values.Length - 1);
-            if (iv2 >= iv1)
-                iv2++;
-            values[iv1] = DvInt4.NA;
-            values[iv2] = DvInt4.NA;
-            Array.Sort(values);
-
-            Assert.True(values[0].IsNA);
-            Assert.True(values[1].IsNA);
-            Assert.True(!values[2].IsNA);
-
-            Assert.True((values[0] == values[1]).IsNA);
-            Assert.True((values[0] != values[1]).IsNA);
-            Assert.True((values[0] <= values[1]).IsNA);
-            Assert.True(values[0].Equals(values[1]));
-            Assert.True(values[0].CompareTo(values[1]) == 0);
-
-            Assert.True((values[1] == values[2]).IsNA);
-            Assert.True((values[1] != values[2]).IsNA);
-            Assert.True((values[1] <= values[2]).IsNA);
-            Assert.True(!values[1].Equals(values[2]));
-            Assert.True(values[1].CompareTo(values[2]) < 0);
-
-            for (int i = 3; i < values.Length; i++)
-            {
-                DvBool eq = values[i - 1] == values[i];
-                DvBool ne = values[i - 1] != values[i];
-                DvBool le = values[i - 1] <= values[i];
-                bool feq = values[i - 1].Equals(values[i]);
-                int cmp = values[i - 1].CompareTo(values[i]);
-                Assert.True(!eq.IsNA);
-                Assert.True(!ne.IsNA);
-                Assert.True(eq.IsTrue == ne.IsFalse);
-                Assert.True(le.IsTrue);
-                Assert.True(feq == eq.IsTrue);
-                Assert.True(cmp <= 0);
-                Assert.True(feq == (cmp == 0));
-            }
-        }
 
         [Fact]
         public void TestComparableDvText()
@@ -114,20 +60,6 @@ public void TestComparableDvText()
             Assert.True((values[1] != values[2]).IsNA);
             Assert.True(!values[1].Equals(values[2]));
             Assert.True(values[1].CompareTo(values[2]) < 0);
-
-            for (int i = 3; i < values.Length; i++)
-            {
-                DvBool eq = values[i - 1] == values[i];
-                DvBool ne = values[i - 1] != values[i];
-                bool feq = values[i - 1].Equals(values[i]);
-                int cmp = values[i - 1].CompareTo(values[i]);
-                Assert.True(!eq.IsNA);
-                Assert.True(!ne.IsNA);
-                Assert.True(eq.IsTrue == ne.IsFalse);
-                Assert.True(feq == eq.IsTrue);
-                Assert.True(cmp <= 0);
-                Assert.True(feq == (cmp == 0));
-            }
         }
     }
 }
diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
index 34922a4ab1..845bfcf6e9 100644
--- a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
+++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
@@ -345,9 +345,9 @@ public void TestCrossValidationMacro()
                 {
                     var getter = cursor.GetGetter<double>(metricCol);
                     var foldGetter = cursor.GetGetter<DvText>(foldCol);
-                    var isWeightedGetter = cursor.GetGetter<DvBool>(isWeightedCol);
+                    var isWeightedGetter = cursor.GetGetter<bool>(isWeightedCol);
                     DvText fold = default;
-                    DvBool isWeighted = default;
+                    bool isWeighted = default;
 
                     double avg = 0;
                     double weightedAvg = 0;
@@ -363,7 +363,7 @@ public void TestCrossValidationMacro()
                         foldGetter(ref fold);
                         Assert.True(fold.EqualsStr("Average"));
                         isWeightedGetter(ref isWeighted);
-                        Assert.True(isWeighted.IsTrue == (w == 1));
+                        Assert.True(isWeighted == (w == 1));
 
                         // Get the standard deviation.
                         b = cursor.MoveNext();
@@ -377,7 +377,7 @@ public void TestCrossValidationMacro()
                         else
                             Assert.Equal(0.000393, stdev, 6);
                         isWeightedGetter(ref isWeighted);
-                        Assert.True(isWeighted.IsTrue == (w == 1));
+                        Assert.True(isWeighted == (w == 1));
                     }
                     double sum = 0;
                     double weightedSum = 0;
@@ -396,7 +396,7 @@ public void TestCrossValidationMacro()
                                 sum += val;
                             Assert.True(fold.EqualsStr("Fold " + f));
                             isWeightedGetter(ref isWeighted);
-                            Assert.True(isWeighted.IsTrue == (w == 1));
+                            Assert.True(isWeighted == (w == 1));
                         }
                     }
                     Assert.Equal(weightedAvg, weightedSum / 2);
diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs
index c44678bf07..60c53ecdbe 100644
--- a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs
+++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs
@@ -1017,13 +1017,13 @@ public void EntryPointPipelineEnsembleText()
                 InputFile = inputFile
             }).Data;
 
-            ValueMapper<DvText, DvBool> labelToBinary =
-                (ref DvText src, ref DvBool dst) =>
+            ValueMapper<DvText, bool> labelToBinary =
+                (ref DvText src, ref bool dst) =>
                 {
                     if (src.EqualsStr("Sport"))
-                        dst = DvBool.True;
+                        dst = true;
                     else
-                        dst = DvBool.False;
+                        dst = false;
                 };
             dataView = LambdaColumnMapper.Create(Env, "TextToBinaryLabel", dataView, "Label", "Label",
                 TextType.Instance, BoolType.Instance, labelToBinary);
diff --git a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
index 059443c57d..f54cb4cd6c 100644
--- a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
+++ b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs
@@ -637,23 +637,23 @@ private void CombineAndTestTreeEnsembles(IDataView idv, IPredictorModel[] fastTr
             {
                 var scoreGetter = curs.GetGetter<float>(scoreCol);
                 var probGetter = curs.GetGetter<float>(probCol);
-                var predGetter = curs.GetGetter<DvBool>(predCol);
+                var predGetter = curs.GetGetter<bool>(predCol);
                 var scoreGetters = new ValueGetter<float>[3];
                 var probGetters = new ValueGetter<float>[3];
-                var predGetters = new ValueGetter<DvBool>[3];
+                var predGetters = new ValueGetter<bool>[3];
                 for (int i = 0; i < 3; i++)
                 {
                     scoreGetters[i] = cursors[i].GetGetter<float>(scoreColArray[i]);
                     probGetters[i] = cursors[i].GetGetter<float>(probColArray[i]);
-                    predGetters[i] = cursors[i].GetGetter<DvBool>(predColArray[i]);
+                    predGetters[i] = cursors[i].GetGetter<bool>(predColArray[i]);
                 }
 
                 float score = 0;
                 float prob = 0;
-                var pred = default(DvBool);
+                bool pred = default;
                 var scores = new float[3];
                 var probs = new float[3];
-                var preds = new DvBool[3];
+                var preds = new bool[3];
                 while (curs.MoveNext())
                 {
                     scoreGetter(ref score);
@@ -668,7 +668,7 @@ private void CombineAndTestTreeEnsembles(IDataView idv, IPredictorModel[] fastTr
                     }
                     Assert.Equal(score, 0.4 * scores.Sum() / 3, 5);
                     Assert.Equal(prob, 1 / (1 + Math.Exp(-score)), 6);
-                    Assert.True(pred.IsTrue == score > 0);
+                    Assert.True(pred == score > 0);
                 }
             }
         }
diff --git a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs
index b53062c1a8..260ee800d8 100644
--- a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs
+++ b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs
@@ -904,7 +904,7 @@ protected Func<bool> GetColumnComparer(IRow r1, IRow r2, int col, ColumnType typ
                 case DataKind.Text:
                     return GetComparerOne<DvText>(r1, r2, col, DvText.Identical);
                 case DataKind.Bool:
-                    return GetComparerOne<DvBool>(r1, r2, col, (x, y) => x.Equals(y));
+                    return GetComparerOne<bool>(r1, r2, col, (x, y) => x == y);
                 case DataKind.TimeSpan:
                     return GetComparerOne<DvTimeSpan>(r1, r2, col, (x, y) => x.Equals(y));
                 case DataKind.DT:
@@ -947,7 +947,7 @@ protected Func<bool> GetColumnComparer(IRow r1, IRow r2, int col, ColumnType typ
                 case DataKind.Text:
                     return GetComparerVec<DvText>(r1, r2, col, size, DvText.Identical);
                 case DataKind.Bool:
-                    return GetComparerVec<DvBool>(r1, r2, col, size, (x, y) => x.Equals(y));
+                    return GetComparerVec<bool>(r1, r2, col, size, (x, y) => x == y);
                 case DataKind.TimeSpan:
                     return GetComparerVec<DvTimeSpan>(r1, r2, col, size, (x, y) => x.Equals(y));
                 case DataKind.DT:
diff --git a/test/Microsoft.ML.TestFramework/TestSparseDataView.cs b/test/Microsoft.ML.TestFramework/TestSparseDataView.cs
index 08c9e17a28..7154bf10fc 100644
--- a/test/Microsoft.ML.TestFramework/TestSparseDataView.cs
+++ b/test/Microsoft.ML.TestFramework/TestSparseDataView.cs
@@ -35,7 +35,7 @@ public void SparseDataView()
         {
             GenericSparseDataView(new[] { 1f, 2f, 3f }, new[] { 1f, 10f, 100f });
             GenericSparseDataView(new DvInt4[] { 1, 2, 3 }, new DvInt4[] { 1, 10, 100 });
-            GenericSparseDataView(new DvBool[] { true, true, true }, new DvBool[] { false, false, false });
+            GenericSparseDataView(new bool[] { true, true, true }, new bool[] { false, false, false });
             GenericSparseDataView(new double[] { 1, 2, 3 }, new double[] { 1, 10, 100 });
             GenericSparseDataView(new DvText[] { new DvText("a"), new DvText("b"), new DvText("c") },
                                   new DvText[] { new DvText("aa"), new DvText("bb"), new DvText("cc") });
@@ -77,7 +77,7 @@ public void DenseDataView()
         {
             GenericDenseDataView(new[] { 1f, 2f, 3f }, new[] { 1f, 10f, 100f });
             GenericDenseDataView(new DvInt4[] { 1, 2, 3 }, new DvInt4[] { 1, 10, 100 });
-            GenericDenseDataView(new DvBool[] { true, true, true }, new DvBool[] { false, false, false });
+            GenericDenseDataView(new bool[] { true, true, true }, new bool[] { false, false, false });
             GenericDenseDataView(new double[] { 1, 2, 3 }, new double[] { 1, 10, 100 });
             GenericDenseDataView(new DvText[] { new DvText("a"), new DvText("b"), new DvText("c") },
                                  new DvText[] { new DvText("aa"), new DvText("bb"), new DvText("cc") });
diff --git a/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs b/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs
index 14a7f473f7..23fe30bd74 100644
--- a/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs
+++ b/test/Microsoft.ML.Tests/CollectionDataSourceTests.cs
@@ -309,7 +309,6 @@ public class ConversionNullalbeClass
             public ulong? fuLong;
             public float? fFloat;
             public double? fDouble;
-            public bool? fBool;
             public string fString;
         }
 
@@ -440,7 +439,6 @@ public void RoundTripConversionWithBasicTypes()
                 {
                     fInt = int.MaxValue - 1,
                     fuInt = uint.MaxValue - 1,
-                    fBool = true,
                     fsByte = sbyte.MaxValue - 1,
                     fByte = byte.MaxValue - 1,
                     fDouble = double.MaxValue - 1,
@@ -455,7 +453,6 @@ public void RoundTripConversionWithBasicTypes()
                 {
                     fInt = int.MaxValue,
                     fuInt = uint.MaxValue,
-                    fBool = true,
                     fsByte = sbyte.MaxValue,
                     fByte = byte.MaxValue,
                     fDouble = double.MaxValue,
@@ -470,7 +467,6 @@ public void RoundTripConversionWithBasicTypes()
                 {
                     fInt = int.MinValue + 1,
                     fuInt = uint.MinValue,
-                    fBool = false,
                     fsByte = sbyte.MinValue + 1,
                     fByte = byte.MinValue,
                     fDouble = double.MinValue + 1,
@@ -784,7 +780,6 @@ public class ClassWithNullableArrays
             public ulong?[] fuLong;
             public float?[] fFloat;
             public double?[] fDouble;
-            public bool?[] fBool;
         }
 
         [Fact]
@@ -819,7 +814,6 @@ public void RoundTripConversionWithArrays()
                     fInt = new int?[3] { null, -1, 1 },
                     fFloat = new float?[3] { -0.99f, null, 0.99f },
                     fString = new string[2] { null, "" },
-                    fBool = new bool?[3] { true, null, false },
                     fByte = new byte?[4] { 0, 125, null, 255 },
                     fDouble = new double?[3] { -1, null, 1 },
                     fLong = new long?[] { null, -1, 1 },
@@ -895,7 +889,6 @@ public class ClassWithNullableArrayProperties
             private ulong?[] _fuLong;
             private float?[] _fFloat;
             private double?[] _fDouble;
-            private bool?[] _fBool;
 
             public string[] StringProp { get { return _fString; } set { _fString = value; } }
             public int?[] IntProp { get { return _fInt; } set { _fInt = value; } }
@@ -908,7 +901,6 @@ public class ClassWithNullableArrayProperties
             public ulong?[] ULongProp { get { return _fuLong; } set { _fuLong = value; } }
             public float?[] SingleProp { get { return _fFloat; } set { _fFloat = value; } }
             public double?[] DoubleProp { get { return _fDouble; } set { _fDouble = value; } }
-            public bool?[] BoolProp { get { return _fBool; } set { _fBool = value; } }
         }
 
         [Fact]
@@ -943,7 +935,6 @@ public void RoundTripConversionWithArrayPropertiess()
                     IntProp = new int?[3] { null, -1, 1 },
                     SingleProp = new float?[3] { -0.99f, null, 0.99f },
                     StringProp = new string[2] { null, "" },
-                    BoolProp = new bool?[3] { true, null, false },
                     ByteProp = new byte?[4] { 0, 125, null, 255 },
                     DoubleProp = new double?[3] { -1, null, 1 },
                     LongProp = new long?[] { null, -1, 1 },
diff --git a/test/Microsoft.ML.Tests/LearningPipelineTests.cs b/test/Microsoft.ML.Tests/LearningPipelineTests.cs
index f19e3285d7..6850119d8c 100644
--- a/test/Microsoft.ML.Tests/LearningPipelineTests.cs
+++ b/test/Microsoft.ML.Tests/LearningPipelineTests.cs
@@ -94,7 +94,7 @@ public class Data
         public class Prediction
         {
             [ColumnName("PredictedLabel")]
-            public DvBool PredictedLabel;
+            public bool PredictedLabel;
         }
 
         [Fact]
@@ -137,36 +137,6 @@ public void BooleanLabelPipeline()
             var model = pipeline.Train<Data, Prediction>();
         }
 
-        public class NullableBooleanLabelData
-        {
-            [ColumnName("Features")]
-            [VectorType(2)]
-            public float[] Features;
-
-            [ColumnName("Label")]
-            public bool? Label;
-        }
-
-        [Fact]
-        public void NullableBooleanLabelPipeline()
-        {
-            var data = new NullableBooleanLabelData[2];
-            data[0] = new NullableBooleanLabelData
-            {
-                Features = new float[] { 0.0f, 1.0f },
-                Label = null
-            };
-            data[1] = new NullableBooleanLabelData
-            {
-                Features = new float[] { 1.0f, 0.0f },
-                Label = false
-            };
-            var pipeline = new LearningPipeline();
-            pipeline.Add(CollectionDataSource.Create(data));
-            pipeline.Add(new FastForestBinaryClassifier());
-            var model = pipeline.Train<Data, Prediction>();
-        }
-
         [Fact]
         public void AppendPipeline()
         {
diff --git a/test/Microsoft.ML.Tests/OnnxTests.cs b/test/Microsoft.ML.Tests/OnnxTests.cs
index d9c05ddcc1..b97b8c449e 100644
--- a/test/Microsoft.ML.Tests/OnnxTests.cs
+++ b/test/Microsoft.ML.Tests/OnnxTests.cs
@@ -41,7 +41,7 @@ public class BreastCancerDataAllColumns
         public class BreastCancerPrediction
         {
             [ColumnName("PredictedLabel")]
-            public DvBool Cancerous;
+            public bool Cancerous;
         }
 
         public class BreastCancerMCPrediction
diff --git a/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs b/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs
index 4d522c6f4d..c1aa92f757 100644
--- a/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs
+++ b/test/Microsoft.ML.Tests/Scenarios/SentimentPredictionTests.cs
@@ -178,13 +178,13 @@ public void CrossValidateSentimentModelTest()
             var sentiments = GetTestData();
             var predictions = cv.PredictorModels[0].Predict(sentiments);
             Assert.Equal(2, predictions.Count());
-            Assert.True(predictions.ElementAt(0).Sentiment.IsTrue);
-            Assert.True(predictions.ElementAt(1).Sentiment.IsTrue);
+            Assert.True(predictions.ElementAt(0).Sentiment);
+            Assert.True(predictions.ElementAt(1).Sentiment);
 
             predictions = cv.PredictorModels[1].Predict(sentiments);
             Assert.Equal(2, predictions.Count());
-            Assert.True(predictions.ElementAt(0).Sentiment.IsTrue);
-            Assert.True(predictions.ElementAt(1).Sentiment.IsTrue);
+            Assert.True(predictions.ElementAt(0).Sentiment);
+            Assert.True(predictions.ElementAt(1).Sentiment);
         }
 
         private void ValidateBinaryMetricsSymSGD(BinaryClassificationMetrics metrics)
@@ -438,8 +438,8 @@ private void ValidateExamples(PredictionModel<SentimentData, SentimentPrediction
             var predictions = model.Predict(sentiments);
             Assert.Equal(2, predictions.Count());
 
-            Assert.True(predictions.ElementAt(0).Sentiment.IsTrue);
-            Assert.True(predictions.ElementAt(1).Sentiment.IsTrue);
+            Assert.True(predictions.ElementAt(0).Sentiment);
+            Assert.True(predictions.ElementAt(1).Sentiment);
 
         }
 
@@ -449,8 +449,8 @@ private void ValidateExamplesLightGBM(PredictionModel<SentimentData, SentimentPr
             var predictions = model.Predict(sentiments);
             Assert.Equal(2, predictions.Count());
 
-            Assert.True(predictions.ElementAt(0).Sentiment.IsTrue);
-            Assert.True(predictions.ElementAt(1).Sentiment.IsTrue);
+            Assert.True(predictions.ElementAt(0).Sentiment);
+            Assert.True(predictions.ElementAt(1).Sentiment);
         }
 
         private void ValidateExamplesSymSGD(PredictionModel<SentimentData, SentimentPrediction> model)
@@ -459,8 +459,8 @@ private void ValidateExamplesSymSGD(PredictionModel<SentimentData, SentimentPred
             var predictions = model.Predict(sentiments);
             Assert.Equal(2, predictions.Count());
 
-            Assert.True(predictions.ElementAt(0).Sentiment.IsFalse);
-            Assert.True(predictions.ElementAt(1).Sentiment.IsTrue);
+            Assert.False(predictions.ElementAt(0).Sentiment);
+            Assert.True(predictions.ElementAt(1).Sentiment);
         }
 
         private Data.TextLoader PrepareTextLoaderTestData()
@@ -519,7 +519,7 @@ public class SentimentData
         public class SentimentPrediction
         {
             [ColumnName("PredictedLabel")]
-            public DvBool Sentiment;
+            public bool Sentiment;
         }
     }
 }
diff --git a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs
index 7dd7a0145c..bb56780d8e 100644
--- a/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs
+++ b/test/Microsoft.ML.Tests/ScenariosWithDirectInstantiation/SentimentPredictionTests.cs
@@ -91,8 +91,8 @@ public void TrainAndPredictSentimentModelWithDirectionInstantiationTest()
                 var sentiments = GetTestData();
                 var predictions = model.Predict(sentiments, false);
                 Assert.Equal(2, predictions.Count());
-                Assert.True(predictions.ElementAt(0).Sentiment.IsTrue);
-                Assert.True(predictions.ElementAt(1).Sentiment.IsTrue);
+                Assert.True(predictions.ElementAt(0).Sentiment);
+                Assert.True(predictions.ElementAt(1).Sentiment);
 
                 // Get feature importance based on feature gain during training
                 var summary = ((FeatureWeightsCalibratedPredictor)pred).GetSummaryInKeyValuePairs(trainRoles.Schema);
@@ -185,8 +185,8 @@ public void TrainAndPredictSentimentModelWithDirectionInstantiationTestWithWordE
                 var sentiments = GetTestData();
                 var predictions = model.Predict(sentiments, false);
                 Assert.Equal(2, predictions.Count());
-                Assert.True(predictions.ElementAt(0).Sentiment.IsTrue);
-                Assert.True(predictions.ElementAt(1).Sentiment.IsTrue);
+                Assert.True(predictions.ElementAt(0).Sentiment);
+                Assert.True(predictions.ElementAt(1).Sentiment);
 
                 // Get feature importance based on feature gain during training
                 var summary = ((FeatureWeightsCalibratedPredictor)pred).GetSummaryInKeyValuePairs(trainRoles.Schema);

From 4385afe5607f433c595cfd0978c92acc04a451e0 Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Sat, 18 Aug 2018 16:23:30 -0700
Subject: [PATCH 02/13] temp unblock test failure..

---
 test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
index 845bfcf6e9..80506d023e 100644
--- a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
+++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
@@ -377,7 +377,7 @@ public void TestCrossValidationMacro()
                         else
                             Assert.Equal(0.000393, stdev, 6);
                         isWeightedGetter(ref isWeighted);
-                        Assert.True(isWeighted == (w == 1));
+                        //Assert.True(isWeighted == (w == 1)); @codemzs is investigating this. 
                     }
                     double sum = 0;
                     double weightedSum = 0;

From b0f624a28301959eb67559b2c92a5437195042c8 Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Sat, 18 Aug 2018 17:57:19 -0700
Subject: [PATCH 03/13] clean up.

---
 src/Microsoft.ML.Api/TypedCursor.cs                           | 2 +-
 src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs | 2 +-
 src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs            | 2 +-
 src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs       | 2 +-
 test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs       | 2 +-
 5 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/Microsoft.ML.Api/TypedCursor.cs b/src/Microsoft.ML.Api/TypedCursor.cs
index 8e7e91fe79..e156ebf5c8 100644
--- a/src/Microsoft.ML.Api/TypedCursor.cs
+++ b/src/Microsoft.ML.Api/TypedCursor.cs
@@ -282,7 +282,7 @@ private Action<TRow> GenerateSetter(IRow input, int index, InternalSchemaDefinit
                     else if (fieldType.GetElementType() == typeof(bool))
                     {
                         Ch.Assert(colType.ItemType.IsBool);
-                        return CreateConvertingVBufferSetter<bool, bool>(input, index, poke, peek, x => (bool)x);
+                        return CreateConvertingVBufferSetter<bool, bool>(input, index, poke, peek, x => x);
                     }
                     else if (fieldType.GetElementType() == typeof(int))
                     {
diff --git a/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs b/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs
index 305dfe8478..becd848a16 100644
--- a/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs
+++ b/src/Microsoft.ML.Data/Evaluators/BinaryClassifierEvaluator.cs
@@ -998,7 +998,7 @@ private Double GetLogLoss(Single prob, Single label)
         private bool GetPredictedLabel(Single val)
         {
             //Behavior for NA values is undefined.
-            return val.IsNA() ? false : val > _threshold ? true : false;
+            return val.IsNA() ? false : val > _threshold;
         }
 
         public override RowMapperColumnInfo[] GetOutputColumns()
diff --git a/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs b/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs
index 3bf076fa7b..0d0c19d1ef 100644
--- a/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs
+++ b/src/Microsoft.ML.Data/Evaluators/EvaluatorUtils.cs
@@ -1256,7 +1256,7 @@ internal static IDataView GetAverageToDataView(IHostEnvironment env, ISchema sch
                 else if (i == isWeightedCol)
                 {
                     env.AssertValue(weightedDvBldr);
-                    dvBldr.AddColumn(MetricKinds.ColumnNames.IsWeighted, BoolType.Instance, foldCol >= 0 ? new[] { false, true} : new[] { false });
+                    dvBldr.AddColumn(MetricKinds.ColumnNames.IsWeighted, BoolType.Instance, foldCol >= 0 ? new[] { false, false} : new[] { false });
                     weightedDvBldr.AddColumn(MetricKinds.ColumnNames.IsWeighted, BoolType.Instance, foldCol >= 0 ? new[] { true, true } : new[] { true });
                 }
                 else if (i == foldCol)
diff --git a/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs b/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs
index bf454a0f85..ee76b5a674 100644
--- a/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs
+++ b/src/Microsoft.ML.Data/Scorers/BinaryClassifierScorer.cs
@@ -262,7 +262,7 @@ protected override Delegate GetPredictedLabelGetter(IRow output, out Delegate sc
         private void GetPredictedLabelCore(Float score, ref bool value)
         {
             //Behavior for NA values is undefined.
-            value = score > _threshold ? true : false;
+            value = score > _threshold;
         }
 
         private void GetPredictedLabelCoreAsKey(Float score, ref uint value)
diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
index 80506d023e..845bfcf6e9 100644
--- a/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
+++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestCSharpApi.cs
@@ -377,7 +377,7 @@ public void TestCrossValidationMacro()
                         else
                             Assert.Equal(0.000393, stdev, 6);
                         isWeightedGetter(ref isWeighted);
-                        //Assert.True(isWeighted == (w == 1)); @codemzs is investigating this. 
+                        Assert.True(isWeighted == (w == 1));
                     }
                     double sum = 0;
                     double weightedSum = 0;

From 92cd8c992841b5ea1e4b0320f9d2e831621e3393 Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Sun, 26 Aug 2018 17:13:38 -0700
Subject: [PATCH 04/13] PR feedback.

---
 .../DataViewConstructionUtils.cs              |  11 -
 src/Microsoft.ML.Api/TypedCursor.cs           |  11 -
 src/Microsoft.ML.Core/Data/DvBool.cs          | 226 ------------------
 src/Microsoft.ML.Core/Data/DvText.cs          |  20 +-
 src/Microsoft.ML.Data/Data/Conversion.cs      |   3 +-
 .../Transforms/NormalizeColumn.cs             |   4 +-
 .../NAIndicatorTransform.cs                   |   7 +-
 .../UnitTests/DvTypes.cs                      |   8 +-
 8 files changed, 19 insertions(+), 271 deletions(-)
 delete mode 100644 src/Microsoft.ML.Core/Data/DvBool.cs

diff --git a/src/Microsoft.ML.Api/DataViewConstructionUtils.cs b/src/Microsoft.ML.Api/DataViewConstructionUtils.cs
index edeee7297f..088ca95408 100644
--- a/src/Microsoft.ML.Api/DataViewConstructionUtils.cs
+++ b/src/Microsoft.ML.Api/DataViewConstructionUtils.cs
@@ -171,11 +171,6 @@ private Delegate CreateGetter(int index)
                             Ch.Assert(colType.ItemType == NumberType.I1);
                             return CreateConvertingArrayGetterDelegate<sbyte?, DvInt1>(index, x => x ?? DvInt1.NA);
                         }
-                        else if (outputType.GetElementType() == typeof(bool))
-                        {
-                            Ch.Assert(colType.ItemType.IsBool);
-                            return CreateConvertingArrayGetterDelegate<bool, bool>(index, x => x);
-                        }
 
                         // T[] -> VBuffer<T>
                         if (outputType.GetElementType().IsGenericType && outputType.GetElementType().GetGenericTypeDefinition() == typeof(Nullable<>))
@@ -203,12 +198,6 @@ private Delegate CreateGetter(int index)
                             Ch.Assert(colType.IsText);
                             return CreateConvertingGetterDelegate<String, DvText>(index, x => x == null ? DvText.NA : new DvText(x));
                         }
-                        else if (outputType == typeof(bool))
-                        {
-                            // Bool -> Bool.
-                            Ch.Assert(colType.IsBool);
-                            return CreateConvertingGetterDelegate<bool, bool>(index, x => x);
-                        }
                         else if (outputType == typeof(int))
                         {
                             // int -> DvInt4
diff --git a/src/Microsoft.ML.Api/TypedCursor.cs b/src/Microsoft.ML.Api/TypedCursor.cs
index e156ebf5c8..73664b8ad1 100644
--- a/src/Microsoft.ML.Api/TypedCursor.cs
+++ b/src/Microsoft.ML.Api/TypedCursor.cs
@@ -279,11 +279,6 @@ private Action<TRow> GenerateSetter(IRow input, int index, InternalSchemaDefinit
                         Ch.Assert(colType.ItemType.IsText);
                         return CreateConvertingVBufferSetter<DvText, string>(input, index, poke, peek, x => x.ToString());
                     }
-                    else if (fieldType.GetElementType() == typeof(bool))
-                    {
-                        Ch.Assert(colType.ItemType.IsBool);
-                        return CreateConvertingVBufferSetter<bool, bool>(input, index, poke, peek, x => x);
-                    }
                     else if (fieldType.GetElementType() == typeof(int))
                     {
                         Ch.Assert(colType.ItemType == NumberType.I4);
@@ -352,12 +347,6 @@ private Action<TRow> GenerateSetter(IRow input, int index, InternalSchemaDefinit
                         Ch.Assert(peek == null);
                         return CreateConvertingActionSetter<DvText, string>(input, index, poke, x => x.ToString());
                     }
-                    else if (fieldType == typeof(bool))
-                    {
-                        Ch.Assert(colType.IsBool);
-                        Ch.Assert(peek == null);
-                        return CreateConvertingActionSetter<bool, bool>(input, index, poke, x => x);
-                    }
                     else if (fieldType == typeof(int))
                     {
                         Ch.Assert(colType == NumberType.I4);
diff --git a/src/Microsoft.ML.Core/Data/DvBool.cs b/src/Microsoft.ML.Core/Data/DvBool.cs
deleted file mode 100644
index f17cb596d4..0000000000
--- a/src/Microsoft.ML.Core/Data/DvBool.cs
+++ /dev/null
@@ -1,226 +0,0 @@
-// Licensed to the .NET Foundation under one or more agreements.
-// The .NET Foundation licenses this file to you under the MIT license.
-// See the LICENSE file in the project root for more information.
-
-using System;
-using System.Runtime.CompilerServices;
-
-namespace Microsoft.ML.Runtime.Data
-{
-    using BL = DvBool;
-    using R4 = Single;
-    using R8 = Double;
-
-    public struct DvBool : IEquatable<DvBool>, IComparable<DvBool>
-    {
-        private const byte _false = 0;
-        private const byte _true = 1;
-        private const byte _na = 128;
-        public const byte RawNA = _na;
-
-        private byte _value;
-
-        public static BL False { get { BL res; res._value = _false; return res; } }
-        public static BL True { get { BL res; res._value = _true; return res; } }
-        public static BL NA { get { BL res; res._value = _na; return res; } }
-
-        /// <summary>
-        /// Property to return the raw value.
-        /// </summary>
-        public byte RawValue
-        {
-            [MethodImpl(MethodImplOptions.AggressiveInlining)]
-            get { return _value; }
-        }
-
-        /// <summary>
-        /// Static method to return the raw value. This is more convenient than the
-        /// property in code-generation scenarios.
-        /// </summary>
-        public static byte GetRawBits(BL a)
-        {
-            return a._value;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        private DvBool(int value)
-        {
-            Contracts.Assert(value == _true || value == _false || value == _na);
-            _value = (byte)value;
-        }
-
-        /// <summary>
-        /// Returns whether this value is false.
-        /// </summary>
-        public bool IsFalse
-        {
-            [MethodImpl(MethodImplOptions.AggressiveInlining)]
-            get { return _value == _false; }
-        }
-
-        /// <summary>
-        /// Returns whether this value is true.
-        /// </summary>
-        public bool IsTrue
-        {
-            [MethodImpl(MethodImplOptions.AggressiveInlining)]
-            get { return _value == _true; }
-        }
-
-        /// <summary>
-        /// Returns whether this value is NA.
-        /// </summary>
-        public bool IsNA
-        {
-            [MethodImpl(MethodImplOptions.AggressiveInlining)]
-            get { return _value > _true; }
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static implicit operator BL(bool value)
-        {
-            BL res;
-            res._value = value ? _true : _false;
-            return res;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static implicit operator BL(bool? value)
-        {
-            BL res;
-            res._value = value == null ? _na : value.GetValueOrDefault() ? _true : _false;
-            return res;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static explicit operator bool(BL value)
-        {
-            switch (value._value)
-            {
-            case _false:
-                return false;
-            case _true:
-                return true;
-            default:
-                throw Contracts.ExceptValue(nameof(value), "NA cast to bool");
-            }
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static explicit operator bool?(BL value)
-        {
-            switch (value._value)
-            {
-            case _false:
-                return false;
-            case _true:
-                return true;
-            default:
-                return null;
-            }
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static explicit operator R4(BL value)
-        {
-            if (value._value <= _true)
-                return value._value;
-            return Single.NaN;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static explicit operator R8(BL value)
-        {
-            if (value._value <= _true)
-                return value._value;
-            return Double.NaN;
-        }
-
-        public override int GetHashCode()
-        {
-            return _value.GetHashCode();
-        }
-
-        public override bool Equals(object obj)
-        {
-            if (obj is BL)
-                return _value == ((BL)obj)._value;
-            return false;
-        }
-
-        public bool Equals(BL other)
-        {
-            // Note that if one or both are "non-standard" NA values, this
-            // could return false. Theoretically, that should never happen,
-            // but unsafe code could cause it.
-            return _value == other._value;
-        }
-
-        public int CompareTo(BL other)
-        {
-            // Note that if one or both are "non-standard" NA values, this could produce unexpected comparisons.
-            // Theoretically, that should never happen, but unsafe code could cause it.
-            Contracts.Assert(unchecked((sbyte)RawNA) < (sbyte)_false);
-            if (_value == other._value)
-                return 0;
-            return (sbyte)_value < (sbyte)other._value ? -1 : 1;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator ==(BL a, BL b)
-        {
-            if (a._value <= _true && b._value <= _true)
-                return a._value == b._value ? True : False;
-            return NA;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator !=(BL a, BL b)
-        {
-            if (a._value <= _true && b._value <= _true)
-                return a._value != b._value ? True : False;
-            return NA;
-        }
-
-        public override string ToString()
-        {
-            if (_value == _false)
-                return "False";
-            if (_value == _true)
-                return "True";
-            return "NA";
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator !(BL a)
-        {
-            if (a._value <= _true)
-                a._value ^= 1;
-            return a;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator |(BL a, BL b)
-        {
-            if (a._value == _true)
-                return a;
-            if (b._value == _true)
-                return b;
-            if (a._value != _false)
-                return a;
-            return b;
-        }
-
-        [MethodImpl(MethodImplOptions.AggressiveInlining)]
-        public static BL operator &(BL a, BL b)
-        {
-            if (a._value == _false)
-                return a;
-            if (b._value == _false)
-                return b;
-            if (a._value != _true)
-                return a;
-            return b;
-        }
-    }
-}
diff --git a/src/Microsoft.ML.Core/Data/DvText.cs b/src/Microsoft.ML.Core/Data/DvText.cs
index 04d3bd8918..593a1ef022 100644
--- a/src/Microsoft.ML.Core/Data/DvText.cs
+++ b/src/Microsoft.ML.Core/Data/DvText.cs
@@ -139,37 +139,37 @@ public string GetRawUnderlyingBufferInfo(out int ichMin, out int ichLim)
         /// <summary>
         /// This compares the two text values with NA propagation semantics.
         /// </summary>
-        public static DvBool operator ==(DvText a, DvText b)
+        public static bool operator ==(DvText a, DvText b)
         {
             if (a.IsNA || b.IsNA)
-                return DvBool.NA;
+                return false;
 
             if (a.Length != b.Length)
-                return DvBool.False;
+                return false;
             for (int i = 0; i < a.Length; i++)
             {
                 if (a._outerBuffer[a._ichMin + i] != b._outerBuffer[b._ichMin + i])
-                    return DvBool.False;
+                    return false;
             }
-            return DvBool.True;
+            return false;
         }
 
         /// <summary>
         /// This compares the two text values with NA propagation semantics.
         /// </summary>
-        public static DvBool operator !=(DvText a, DvText b)
+        public static bool operator !=(DvText a, DvText b)
         {
             if (a.IsNA || b.IsNA)
-                return DvBool.NA;
+                return false;
 
             if (a.Length != b.Length)
-                return DvBool.True;
+                return true;
             for (int i = 0; i < a.Length; i++)
             {
                 if (a._outerBuffer[a._ichMin + i] != b._outerBuffer[b._ichMin + i])
-                    return DvBool.True;
+                    return true;
             }
-            return DvBool.False;
+            return false;
         }
 
         public override int GetHashCode()
diff --git a/src/Microsoft.ML.Data/Data/Conversion.cs b/src/Microsoft.ML.Data/Data/Conversion.cs
index 4cc7b0e8f9..8c716622f5 100644
--- a/src/Microsoft.ML.Data/Data/Conversion.cs
+++ b/src/Microsoft.ML.Data/Data/Conversion.cs
@@ -11,7 +11,6 @@
 using System.Text;
 using System.Threading;
 using Microsoft.ML.Runtime.Internal.Utilities;
-using System.Runtime.CompilerServices;
 
 namespace Microsoft.ML.Runtime.Data.Conversion
 {
@@ -1033,7 +1032,7 @@ public void Convert(ref BL src, ref SB dst)
             ClearDst(ref dst);
             if (!src)
                 dst.Append("0");
-            else if (src)
+            else
                 dst.Append("1");
         }
         public void Convert(ref TS src, ref SB dst) { ClearDst(ref dst); if (!src.IsNA) dst.AppendFormat("{0:c}", (TimeSpan)src); }
diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs b/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs
index 5b827b9904..75da6046a9 100644
--- a/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs
+++ b/src/Microsoft.ML.Data/Transforms/NormalizeColumn.cs
@@ -596,7 +596,7 @@ public override void AttachMetadata(MetadataDispatcher.Builder bldr, ColumnType
                     Host.Check(typeSrc.RawType == typeof(TFloat));
                     bldr.AddPrimitive("CdfMean", typeSrc, Mean);
                     bldr.AddPrimitive("CdfStdDev", typeSrc, Stddev);
-                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, (bool)UseLog);
+                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, UseLog);
                 }
             }
 
@@ -625,7 +625,7 @@ public override void AttachMetadata(MetadataDispatcher.Builder bldr, ColumnType
                     Host.Check(typeSrc.ItemType.RawType == typeof(TFloat));
                     bldr.AddGetter<VBuffer<TFloat>>("CdfMean", typeSrc, MeanMetadataGetter);
                     bldr.AddGetter<VBuffer<TFloat>>("CdfStdDev", typeSrc, StddevMetadataGetter);
-                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, (bool)UseLog);
+                    bldr.AddPrimitive("CdfUseLog", BoolType.Instance, UseLog);
                 }
 
                 private void MeanMetadataGetter(int col, ref VBuffer<TFloat> dst)
diff --git a/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs b/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs
index 950a8ccce3..39b3d650d2 100644
--- a/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs
+++ b/src/Microsoft.ML.Transforms/NAIndicatorTransform.cs
@@ -367,21 +367,18 @@ private void FillValues(int srcLength, ref VBuffer<bool> dst, List<int> indices,
                 indices.Add(srcLength);
 
                 int ii = 0;
-                // Assigns values correctly depending on the sense.
-                bool hit = sense;
-                bool miss = !sense;
                 for (int i = 0; i < srcLength; i++)
                 {
                     Host.Assert(0 <= i && i <= indices[ii]);
                     if (i == indices[ii])
                     {
-                        dstValues[i] = hit;
+                        dstValues[i] = sense;
                         ii++;
                         Host.Assert(ii < indices.Count);
                         Host.Assert(indices[ii - 1] < indices[ii]);
                     }
                     else
-                        dstValues[i] = miss;
+                        dstValues[i] = !sense;
                 }
 
                 dst = new VBuffer<bool>(srcLength, dstValues, dstIndices);
diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs b/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs
index ed71fa97f5..e856fa979e 100644
--- a/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs
+++ b/test/Microsoft.ML.Core.Tests/UnitTests/DvTypes.cs
@@ -51,13 +51,13 @@ public void TestComparableDvText()
             Assert.True(values[1].IsNA);
             Assert.True(values[2].IsEmpty);
 
-            Assert.True((values[0] == values[1]).IsNA);
-            Assert.True((values[0] != values[1]).IsNA);
+            Assert.True(!(values[0] == values[1]));
+            Assert.True(!(values[0] != values[1]));
             Assert.True(values[0].Equals(values[1]));
             Assert.True(values[0].CompareTo(values[1]) == 0);
 
-            Assert.True((values[1] == values[2]).IsNA);
-            Assert.True((values[1] != values[2]).IsNA);
+            Assert.True(!(values[1] == values[2]));
+            Assert.True(!(values[1] != values[2]));
             Assert.True(!values[1].Equals(values[2]));
             Assert.True(values[1].CompareTo(values[2]) < 0);
         }

From bac96011255250d61e1395ae2d1108f32ea1b3ef Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Mon, 27 Aug 2018 22:05:38 -0700
Subject: [PATCH 05/13] changes.

---
 src/Microsoft.ML.Data/Data/Conversion.cs |   9 +++------
 test/data/datatypes.idv                  | Bin 809 -> 801 bytes
 2 files changed, 3 insertions(+), 6 deletions(-)

diff --git a/src/Microsoft.ML.Data/Data/Conversion.cs b/src/Microsoft.ML.Data/Data/Conversion.cs
index 8c716622f5..cfa73c284f 100644
--- a/src/Microsoft.ML.Data/Data/Conversion.cs
+++ b/src/Microsoft.ML.Data/Data/Conversion.cs
@@ -1613,11 +1613,7 @@ private U8 ParseU8(ref TX span)
         public bool TryParse(ref TX src, out BL dst)
         {
             // NA text fails.
-            if (src.IsNA)
-            {
-                dst = false;
-                return true;
-            }
+            Contracts.Check(!src.IsNA, "Missing text value cannot be converted to boolean value.");
 
             char ch;
             switch (src.Length)
@@ -1721,7 +1717,8 @@ public bool TryParse(ref TX src, out BL dst)
             }
 
             dst = false;
-            return IsStdMissing(ref src);
+            Contracts.Check(!IsStdMissing(ref src), "Missing text value cannot be converted to boolean value.");
+            return true;
         }
 
         private bool TryParse(ref TX src, out TX dst)
diff --git a/test/data/datatypes.idv b/test/data/datatypes.idv
index 15f12b97484b09de15d051c78a494ed29357198b..e2c7a8543b03bd9327f623c400e3030cfd5634ff 100644
GIT binary patch
literal 801
zcmZ?v^<i)cb7Ej+U<5-L&CbLC29nGWngv2Ja6;+fLIo!#Brq_n&d&jozyJTQw^e3#
zW@ctFW?)Fp*db%oIkB<v;KNQgW^Ex}R)%Dt;smxNGmbol%b7oaicSq>NKR;AYEQRb
zrZwl;fdvbJX2hSrap1y%13>)=JF1tP{$pZiX5(c9nk~=sN>cK`f=0%vX~4i^1Y#gy
z17c9nvZ3(<pnNW%90w5dK>2(?wg3=kK>7SYwgM1KLHWW^z5|pGQmX;PQBXcezXA~J
zBB_@K@|luy*j&n-^7C^T7+K1pl0b1VV9GRP4R)$5Nd?NaW5^k?dghfFngQjeW5}6+
z<cy7ga?3H~EI@K*CP2CE=yD~+93h#xslf$_c|hsoXwu9nCHZ_VWiE*&sUTHR`FS9R
nT}M;Jlv2WlPy|%)99=<41xH9~MG4fF?`YBtPGK$#KEBQX(L-6D

literal 809
zcmZ?v^<i)cb7Ej+U<5-L&CkRD28zrOniWDZa6;+fLIo!#B``4jjz53nz=Z<`4qO1T
z|NpPIRc3Z(W@c%2U}jjIpOcWmz>u7=L&m6cVq@dMhn;TB+CsftQVhun4b1K7*2}c!
zJUg%;(2*IaRi5XSq~w7Gjf_*<8rgsfc2qAn{l~=4%+|{URG*rVkieE?#*x=>IrHaF
z(W#*fz%T~`HXz9Y#EMWpJCF?uayBTR2gv3EVj(D>AIKH~VqYj<0Laz=VJIIY2jbg6
z`GP>U5fH~B=?BT@K>5Nzwmc9sCFQWWlsV<+=P)p`)<Y$M;$Xm(X~-JvR9TV=l<UWk
zGh+43D={<!%FV}+GXcpN8v*6kW5`*6<jhQfa{JNcN{Tr`GILXd3lj5y(&y2nnNv#g
z`CQ6e5=&A+s-p7qKn}Z)riv-0gbSevsNg-if|3f3kkpD2s4f4|q#2yTTo`<OodI@~
BUnBqk


From 9adcf7011d138795f89fae5e0bdb6e697a9a0d2e Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Mon, 27 Aug 2018 23:47:23 -0700
Subject: [PATCH 06/13] changes.

---
 src/Microsoft.ML.Data/Data/Conversion.cs | 11 +++++++----
 1 file changed, 7 insertions(+), 4 deletions(-)

diff --git a/src/Microsoft.ML.Data/Data/Conversion.cs b/src/Microsoft.ML.Data/Data/Conversion.cs
index cfa73c284f..80830f6b10 100644
--- a/src/Microsoft.ML.Data/Data/Conversion.cs
+++ b/src/Microsoft.ML.Data/Data/Conversion.cs
@@ -1612,8 +1612,12 @@ private U8 ParseU8(ref TX span)
         /// </summary>
         public bool TryParse(ref TX src, out BL dst)
         {
-            // NA text fails.
-            Contracts.Check(!src.IsNA, "Missing text value cannot be converted to boolean value.");
+            // NA text -> default.
+            if (src.IsNA)
+            {
+                dst = default;
+                return true;
+            }
 
             char ch;
             switch (src.Length)
@@ -1717,8 +1721,7 @@ public bool TryParse(ref TX src, out BL dst)
             }
 
             dst = false;
-            Contracts.Check(!IsStdMissing(ref src), "Missing text value cannot be converted to boolean value.");
-            return true;
+            return IsStdMissing(ref src);
         }
 
         private bool TryParse(ref TX src, out TX dst)

From 1120e244ee5a262775dfeddaa25a7c3684a4fdda Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Tue, 28 Aug 2018 00:51:44 -0700
Subject: [PATCH 07/13] IDV test update.

---
 src/Microsoft.ML.Data/Data/Conversion.cs      |   2 +-
 .../DataLoadSave/Binary/CodecFactory.cs       |   5 +-
 .../DataLoadSave/Binary/Codecs.cs             | 110 +++++++++++++++---
 .../Command/Datatypes-datatypes.txt           |   4 +-
 .../Command/Datatypes-datatypes.txt           |   4 +-
 test/data/datatypes.idv                       | Bin 801 -> 809 bytes
 6 files changed, 102 insertions(+), 23 deletions(-)

diff --git a/src/Microsoft.ML.Data/Data/Conversion.cs b/src/Microsoft.ML.Data/Data/Conversion.cs
index 80830f6b10..ec2bc2f977 100644
--- a/src/Microsoft.ML.Data/Data/Conversion.cs
+++ b/src/Microsoft.ML.Data/Data/Conversion.cs
@@ -876,7 +876,7 @@ public ValueGetter<T> GetNAOrDefaultGetter<T>(ColumnType type)
         private bool IsDefault(ref R4 src) => src == 0;
         private bool IsDefault(ref R8 src) => src == 0;
         private bool IsDefault(ref TX src) => src.IsEmpty;
-        private bool IsDefault(ref BL src) => !src;
+        private bool IsDefault(ref BL src) => src == default;
         private bool IsDefault(ref U1 src) => src == 0;
         private bool IsDefault(ref U2 src) => src == 0;
         private bool IsDefault(ref U4 src) => src == 0;
diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
index df0d57f3c6..5b8784bf2b 100644
--- a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
+++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
@@ -56,11 +56,14 @@ public CodecFactory(IHostEnvironment env, MemoryStreamPool memPool = null)
             RegisterSimpleCodec(new UnsafeTypeCodec<Double>(this));
             RegisterSimpleCodec(new UnsafeTypeCodec<DvTimeSpan>(this));
             RegisterSimpleCodec(new DvTextCodec(this));
-            RegisterSimpleCodec(new BoolCodec(this));
+            RegisterSimpleCodec(new OldBoolCodec(this));
             RegisterSimpleCodec(new DateTimeCodec(this));
             RegisterSimpleCodec(new DateTimeZoneCodec(this));
             RegisterSimpleCodec(new UnsafeTypeCodec<UInt128>(this));
 
+            // Register the old boolean reading codec.
+            var oldBool = new BoolCodec(this);
+            RegisterOtherCodec("DvBool", oldBool.GetCodec);
             RegisterOtherCodec("VBuffer", GetVBufferCodec);
             RegisterOtherCodec("Key", GetKeyCodec);
         }
diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
index f2ec97ac12..4b526fb233 100644
--- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
+++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
@@ -420,48 +420,53 @@ public override void Get(ref DvText value)
             }
         }
 
-        private sealed class BoolCodec : SimpleCodec<bool>
+        /// <summary>
+        /// This is an older boolean code that reads from a form that serialized
+        /// 1 bit per value. The new encoding (implemented by a different codec)
+        /// uses 2 bits per value so NA values can be supported.
+        /// </summary>
+        private sealed class OldBoolCodec : SimpleCodec<bool>
         {
             // *** Binary block format ***
-            // Pack 32 values into 32 bits, with 0 for false, 1 for true.
+            // Packed bits.
 
-            public BoolCodec(CodecFactory factory)
+            public OldBoolCodec(CodecFactory factory)
                 : base(factory, BoolType.Instance)
             {
             }
 
-            public override IValueWriter<bool> OpenWriter(Stream stream)
+            public override string LoadName
             {
-                return new Writer(this, stream);
+                get { return typeof(bool).Name; }
             }
 
-            public override IValueReader<bool> OpenReader(Stream stream, int items)
+            public override IValueWriter<bool> OpenWriter(Stream stream)
             {
-                return new Reader(this, stream, items);
+                return new Writer(this, stream);
             }
 
             private sealed class Writer : ValueWriterBase<bool>
             {
                 // Pack 16 values into 32 bits.
-                private int _currentBits;
+                private byte _currentBits;
                 private long _numWritten;
-                private int _currentIndex;
+                private byte _currentIndex;
 
-                public Writer(BoolCodec codec, Stream stream)
+                public Writer(OldBoolCodec codec, Stream stream)
                     : base(codec.Factory, stream)
                 {
                 }
 
                 public override void Write(ref bool value)
                 {
-                    Contracts.Assert(0 <= _currentIndex && _currentIndex < 32);
+                    Contracts.Assert(0 <= _currentIndex && _currentIndex < 8);
 
                     _numWritten++;
                     if (value)
-                        _currentBits |= 1 << _currentIndex;
+                        _currentBits |= (byte)(1 << _currentIndex);
 
                     _currentIndex++;
-                    if (_currentIndex == 32)
+                    if (_currentIndex == 8)
                     {
                         Writer.Write(_currentBits);
                         _currentBits = 0;
@@ -487,6 +492,64 @@ public override void Commit()
                 }
             }
 
+            public override IValueReader<bool> OpenReader(Stream stream, int items)
+            {
+                return new Reader(this, stream, items);
+            }
+
+            private sealed class Reader : ValueReaderBase<bool>
+            {
+                private byte _currentBits;
+                private int _currentIndex;
+                private int _remaining;
+
+                public Reader(OldBoolCodec codec, Stream stream, int items)
+                    : base(codec.Factory, stream)
+                {
+                    _remaining = items;
+                    _currentIndex = -1;
+                }
+
+                public override void MoveNext()
+                {
+                    Contracts.Assert(0 < _remaining, "already consumed all values");
+                    --_remaining;
+                    if ((_currentIndex = (_currentIndex + 1) & 7) == 0)
+                        _currentBits = Reader.ReadByte();
+                    else
+                        _currentBits >>= 1;
+                }
+
+                public override void Get(ref bool value)
+                {
+                    Contracts.Assert(0 <= _currentIndex, "have not moved in");
+                    Contracts.Assert(_currentIndex < 8);
+                    value = (_currentBits & 1) != 0;
+                }
+            }
+        }
+
+        private sealed class BoolCodec : SimpleCodec<bool>
+        {
+            // *** Binary block format ***
+            // Pack 16 values into 32 bits, with 00 for false, 01 for true and 10 for NA.
+
+            public BoolCodec(CodecFactory factory)
+                : base(factory, BoolType.Instance)
+            {
+            }
+
+            public override IValueWriter<bool> OpenWriter(Stream stream)
+            {
+                Contracts.Assert(false, "This older form only supports reading");
+                throw Contracts.ExceptNotSupp("Writing single bit booleans no longer supported");
+            }
+
+            public override IValueReader<bool> OpenReader(Stream stream, int items)
+            {
+                return new Reader(this, stream, items);
+            }
+
             private sealed class Reader : ValueReaderBase<bool>
             {
                 private int _currentBits;
@@ -504,17 +567,30 @@ public override void MoveNext()
                 {
                     Contracts.Assert(0 < _remaining, "already consumed all values");
                     --_remaining;
-                    if ((_currentSlot = (_currentSlot + 1) & 0x1F) == 0)
+                    if ((_currentSlot = (_currentSlot + 1) & 0x0F) == 0)
                         _currentBits = Reader.ReadInt32();
                     else
-                        _currentBits = (int)((uint)_currentBits >> 1);
+                        _currentBits = (int)((uint)_currentBits >> 2);
                 }
 
                 public override void Get(ref bool value)
                 {
                     Contracts.Assert(0 <= _currentSlot, "have not moved in");
-                    Contracts.Assert(_currentSlot < 32);
-                    value = Convert.ToBoolean(_currentBits & 0x1);
+                    Contracts.Assert(_currentSlot < 16);
+                    switch (_currentBits & 0x3)
+                    {
+                    case 0x0:
+                        value = false;
+                        break;
+                    case 0x1:
+                        value = true;
+                        break;
+                    case 0x2:
+                        value = false;
+                        break;
+                    default:
+                        throw Contracts.ExceptDecode("Invalid bit pattern in BoolCodec");
+                    }
                 }
             }
         }
diff --git a/test/BaselineOutput/SingleDebug/Command/Datatypes-datatypes.txt b/test/BaselineOutput/SingleDebug/Command/Datatypes-datatypes.txt
index e7d128e400..509a36b3d4 100644
--- a/test/BaselineOutput/SingleDebug/Command/Datatypes-datatypes.txt
+++ b/test/BaselineOutput/SingleDebug/Command/Datatypes-datatypes.txt
@@ -14,6 +14,6 @@
 bl	i1	i2	i4	i8	ts	dto	dt	tx
 0	127	32767	2147483647	9223372036854775807	"2.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	foo
 1	-127	-32767	-2147483647	-9223372036854775807	"7.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	xyz
-					"7.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	
+0					"7.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	
 9	0:0
-								
+0								
diff --git a/test/BaselineOutput/SingleRelease/Command/Datatypes-datatypes.txt b/test/BaselineOutput/SingleRelease/Command/Datatypes-datatypes.txt
index e7d128e400..509a36b3d4 100644
--- a/test/BaselineOutput/SingleRelease/Command/Datatypes-datatypes.txt
+++ b/test/BaselineOutput/SingleRelease/Command/Datatypes-datatypes.txt
@@ -14,6 +14,6 @@
 bl	i1	i2	i4	i8	ts	dto	dt	tx
 0	127	32767	2147483647	9223372036854775807	"2.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	foo
 1	-127	-32767	-2147483647	-9223372036854775807	"7.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	xyz
-					"7.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	
+0					"7.00:00:00"	"2008-11-30T00:00:00.0000000+00:00"	"2013-08-05T00:00:00.0000000"	
 9	0:0
-								
+0								
diff --git a/test/data/datatypes.idv b/test/data/datatypes.idv
index e2c7a8543b03bd9327f623c400e3030cfd5634ff..15f12b97484b09de15d051c78a494ed29357198b 100644
GIT binary patch
literal 809
zcmZ?v^<i)cb7Ej+U<5-L&CkRD28zrOniWDZa6;+fLIo!#B``4jjz53nz=Z<`4qO1T
z|NpPIRc3Z(W@c%2U}jjIpOcWmz>u7=L&m6cVq@dMhn;TB+CsftQVhun4b1K7*2}c!
zJUg%;(2*IaRi5XSq~w7Gjf_*<8rgsfc2qAn{l~=4%+|{URG*rVkieE?#*x=>IrHaF
z(W#*fz%T~`HXz9Y#EMWpJCF?uayBTR2gv3EVj(D>AIKH~VqYj<0Laz=VJIIY2jbg6
z`GP>U5fH~B=?BT@K>5Nzwmc9sCFQWWlsV<+=P)p`)<Y$M;$Xm(X~-JvR9TV=l<UWk
zGh+43D={<!%FV}+GXcpN8v*6kW5`*6<jhQfa{JNcN{Tr`GILXd3lj5y(&y2nnNv#g
z`CQ6e5=&A+s-p7qKn}Z)riv-0gbSevsNg-if|3f3kkpD2s4f4|q#2yTTo`<OodI@~
BUnBqk

literal 801
zcmZ?v^<i)cb7Ej+U<5-L&CbLC29nGWngv2Ja6;+fLIo!#Brq_n&d&jozyJTQw^e3#
zW@ctFW?)Fp*db%oIkB<v;KNQgW^Ex}R)%Dt;smxNGmbol%b7oaicSq>NKR;AYEQRb
zrZwl;fdvbJX2hSrap1y%13>)=JF1tP{$pZiX5(c9nk~=sN>cK`f=0%vX~4i^1Y#gy
z17c9nvZ3(<pnNW%90w5dK>2(?wg3=kK>7SYwgM1KLHWW^z5|pGQmX;PQBXcezXA~J
zBB_@K@|luy*j&n-^7C^T7+K1pl0b1VV9GRP4R)$5Nd?NaW5^k?dghfFngQjeW5}6+
z<cy7ga?3H~EI@K*CP2CE=yD~+93h#xslf$_c|hsoXwu9nCHZ_VWiE*&sUTHR`FS9R
nT}M;Jlv2WlPy|%)99=<41xH9~MG4fF?`YBtPGK$#KEBQX(L-6D


From 1b1f3e2ea4e76322133d03024b2d5b809df5fd35 Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Tue, 28 Aug 2018 01:07:19 -0700
Subject: [PATCH 08/13] cleanup.

---
 .../DataLoadSave/Binary/CodecFactory.cs       |  4 ++--
 .../DataLoadSave/Binary/Codecs.cs             | 20 +++++++++----------
 2 files changed, 12 insertions(+), 12 deletions(-)

diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
index 5b8784bf2b..fc2014294a 100644
--- a/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
+++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/CodecFactory.cs
@@ -56,13 +56,13 @@ public CodecFactory(IHostEnvironment env, MemoryStreamPool memPool = null)
             RegisterSimpleCodec(new UnsafeTypeCodec<Double>(this));
             RegisterSimpleCodec(new UnsafeTypeCodec<DvTimeSpan>(this));
             RegisterSimpleCodec(new DvTextCodec(this));
-            RegisterSimpleCodec(new OldBoolCodec(this));
+            RegisterSimpleCodec(new BoolCodec(this));
             RegisterSimpleCodec(new DateTimeCodec(this));
             RegisterSimpleCodec(new DateTimeZoneCodec(this));
             RegisterSimpleCodec(new UnsafeTypeCodec<UInt128>(this));
 
             // Register the old boolean reading codec.
-            var oldBool = new BoolCodec(this);
+            var oldBool = new OldBoolCodec(this);
             RegisterOtherCodec("DvBool", oldBool.GetCodec);
             RegisterOtherCodec("VBuffer", GetVBufferCodec);
             RegisterOtherCodec("Key", GetKeyCodec);
diff --git a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
index 4b526fb233..e3ff977c02 100644
--- a/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
+++ b/src/Microsoft.ML.Data/DataLoadSave/Binary/Codecs.cs
@@ -421,16 +421,16 @@ public override void Get(ref DvText value)
         }
 
         /// <summary>
-        /// This is an older boolean code that reads from a form that serialized
-        /// 1 bit per value. The new encoding (implemented by a different codec)
+        /// This is a boolean code that reads from a form that serialized
+        /// 1 bit per value. The old encoding (implemented by a different codec)
         /// uses 2 bits per value so NA values can be supported.
         /// </summary>
-        private sealed class OldBoolCodec : SimpleCodec<bool>
+        private sealed class BoolCodec : SimpleCodec<bool>
         {
             // *** Binary block format ***
             // Packed bits.
 
-            public OldBoolCodec(CodecFactory factory)
+            public BoolCodec(CodecFactory factory)
                 : base(factory, BoolType.Instance)
             {
             }
@@ -447,12 +447,12 @@ public override IValueWriter<bool> OpenWriter(Stream stream)
 
             private sealed class Writer : ValueWriterBase<bool>
             {
-                // Pack 16 values into 32 bits.
+                // Pack 8 values into 8 bits.
                 private byte _currentBits;
                 private long _numWritten;
                 private byte _currentIndex;
 
-                public Writer(OldBoolCodec codec, Stream stream)
+                public Writer(BoolCodec codec, Stream stream)
                     : base(codec.Factory, stream)
                 {
                 }
@@ -503,7 +503,7 @@ private sealed class Reader : ValueReaderBase<bool>
                 private int _currentIndex;
                 private int _remaining;
 
-                public Reader(OldBoolCodec codec, Stream stream, int items)
+                public Reader(BoolCodec codec, Stream stream, int items)
                     : base(codec.Factory, stream)
                 {
                     _remaining = items;
@@ -529,12 +529,12 @@ public override void Get(ref bool value)
             }
         }
 
-        private sealed class BoolCodec : SimpleCodec<bool>
+        private sealed class OldBoolCodec : SimpleCodec<bool>
         {
             // *** Binary block format ***
             // Pack 16 values into 32 bits, with 00 for false, 01 for true and 10 for NA.
 
-            public BoolCodec(CodecFactory factory)
+            public OldBoolCodec(CodecFactory factory)
                 : base(factory, BoolType.Instance)
             {
             }
@@ -556,7 +556,7 @@ private sealed class Reader : ValueReaderBase<bool>
                 private int _currentSlot;
                 private int _remaining;
 
-                public Reader(BoolCodec codec, Stream stream, int items)
+                public Reader(OldBoolCodec codec, Stream stream, int items)
                     : base(codec.Factory, stream)
                 {
                     _remaining = items;

From 53b4e57022dd93cdae6c31eb3c5720b585a9aa8c Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Tue, 28 Aug 2018 09:29:52 -0700
Subject: [PATCH 09/13] add test for parquet loader.

---
 .../SavePipe/TestParquetNull-Data.txt         |   9 ++++++++
 .../SavePipe/TestParquetNull-Schema.txt       |   4 ++++
 .../TestParquetPrimitiveDataTypes-Data.txt    |  21 ++++++++++++++++++
 .../TestParquetPrimitiveDataTypes-Schema.txt  |  16 +++++++++++++
 .../SavePipe/TestParquetNull-Data.txt         |   9 ++++++++
 .../SavePipe/TestParquetNull-Schema.txt       |   4 ++++
 .../TestParquetPrimitiveDataTypes-Data.txt    |  21 ++++++++++++++++++
 .../TestParquetPrimitiveDataTypes-Schema.txt  |  16 +++++++++++++
 .../DataPipe/TestDataPipe.cs                  |  20 +++++++++++++++++
 .../Microsoft.ML.TestFramework.csproj         |   1 +
 .../TestInitialization.cs                     |   1 +
 test/data/Parquet/alltypes.parquet            | Bin 0 -> 1419 bytes
 test/data/Parquet/test-null.parquet           | Bin 0 -> 349 bytes
 13 files changed, 122 insertions(+)
 create mode 100644 test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Data.txt
 create mode 100644 test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Schema.txt
 create mode 100644 test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
 create mode 100644 test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
 create mode 100644 test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Data.txt
 create mode 100644 test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Schema.txt
 create mode 100644 test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
 create mode 100644 test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
 create mode 100644 test/data/Parquet/alltypes.parquet
 create mode 100644 test/data/Parquet/test-null.parquet

diff --git a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Data.txt b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Data.txt
new file mode 100644
index 0000000000..c7049cd12a
--- /dev/null
+++ b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Data.txt
@@ -0,0 +1,9 @@
+#@ TextLoader{
+#@   header+
+#@   sep=tab
+#@   col=foo:I4:0
+#@   col=bar:I4:1
+#@ }
+foo	bar
+1	2
+1	
diff --git a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Schema.txt b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Schema.txt
new file mode 100644
index 0000000000..8fa619c171
--- /dev/null
+++ b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetNull-Schema.txt
@@ -0,0 +1,4 @@
+---- ParquetLoader ----
+2 columns:
+  foo: I4
+  bar: I4
diff --git a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
new file mode 100644
index 0000000000..bbdd0c18ab
--- /dev/null
+++ b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
@@ -0,0 +1,21 @@
+#@ TextLoader{
+#@   header+
+#@   sep=tab
+#@   col=Id:I4:0
+#@   col=Timestamp:DZ:1
+#@   col=Message:TX:2
+#@   col=Data:TX:3
+#@   col=IsDeleted:BL:4
+#@   col=Amount:R4:5
+#@   col=TotalAmount:R8:6
+#@   col=Counter:I8:7
+#@   col=Amount2:R8:8
+#@   col=Flag:U1:9
+#@   col=Flag2:I1:10
+#@   col=Flag3:I2:11
+#@   col=Flag4:U2:12
+#@   col=Flag5:TS:13
+#@ }
+Id	Timestamp	Message	Data	IsDeleted	Amount	TotalAmount	Counter	Amount2	Flag	Flag2	Flag3	Flag4	Flag5
+1	"2000-01-01T01:01:01.0000000+00:00"	Record1	SomeData3	0	125.4	400	300000	3331313	3	-3	-600	600	"3100.00:00:00.1000000"
+1	"2000-12-31T23:59:59.9990000+00:00"	Record2	SomeData4	0	126.4	500	400000	4331313	4	-4	-700	700	
diff --git a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
new file mode 100644
index 0000000000..213ef605e6
--- /dev/null
+++ b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
@@ -0,0 +1,16 @@
+---- ParquetLoader ----
+14 columns:
+  Id: I4
+  Timestamp: DateTimeZone
+  Message: Text
+  Data: Text
+  IsDeleted: Bool
+  Amount: R4
+  TotalAmount: R8
+  Counter: I8
+  Amount2: R8
+  Flag: U1
+  Flag2: I1
+  Flag3: I2
+  Flag4: U2
+  Flag5: TimeSpan
diff --git a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Data.txt b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Data.txt
new file mode 100644
index 0000000000..c7049cd12a
--- /dev/null
+++ b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Data.txt
@@ -0,0 +1,9 @@
+#@ TextLoader{
+#@   header+
+#@   sep=tab
+#@   col=foo:I4:0
+#@   col=bar:I4:1
+#@ }
+foo	bar
+1	2
+1	
diff --git a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Schema.txt b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Schema.txt
new file mode 100644
index 0000000000..8fa619c171
--- /dev/null
+++ b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetNull-Schema.txt
@@ -0,0 +1,4 @@
+---- ParquetLoader ----
+2 columns:
+  foo: I4
+  bar: I4
diff --git a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
new file mode 100644
index 0000000000..bbdd0c18ab
--- /dev/null
+++ b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
@@ -0,0 +1,21 @@
+#@ TextLoader{
+#@   header+
+#@   sep=tab
+#@   col=Id:I4:0
+#@   col=Timestamp:DZ:1
+#@   col=Message:TX:2
+#@   col=Data:TX:3
+#@   col=IsDeleted:BL:4
+#@   col=Amount:R4:5
+#@   col=TotalAmount:R8:6
+#@   col=Counter:I8:7
+#@   col=Amount2:R8:8
+#@   col=Flag:U1:9
+#@   col=Flag2:I1:10
+#@   col=Flag3:I2:11
+#@   col=Flag4:U2:12
+#@   col=Flag5:TS:13
+#@ }
+Id	Timestamp	Message	Data	IsDeleted	Amount	TotalAmount	Counter	Amount2	Flag	Flag2	Flag3	Flag4	Flag5
+1	"2000-01-01T01:01:01.0000000+00:00"	Record1	SomeData3	0	125.4	400	300000	3331313	3	-3	-600	600	"3100.00:00:00.1000000"
+1	"2000-12-31T23:59:59.9990000+00:00"	Record2	SomeData4	0	126.4	500	400000	4331313	4	-4	-700	700	
diff --git a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
new file mode 100644
index 0000000000..213ef605e6
--- /dev/null
+++ b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
@@ -0,0 +1,16 @@
+---- ParquetLoader ----
+14 columns:
+  Id: I4
+  Timestamp: DateTimeZone
+  Message: Text
+  Data: Text
+  IsDeleted: Bool
+  Amount: R4
+  TotalAmount: R8
+  Counter: I8
+  Amount2: R8
+  Flag: U1
+  Flag2: I1
+  Flag3: I2
+  Flag4: U2
+  Flag5: TimeSpan
diff --git a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
index c598879795..ba0749318b 100644
--- a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
+++ b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
@@ -145,4 +145,24 @@ public void TestLdaTransformEmptyDocumentException()
             Assert.True(false, "The LDA transform does not throw expected error on empty documents.");
         }
     }
+
+    public sealed partial class TestDataPipe : TestDataPipeBase
+    {
+
+        [Fact]
+        public void TestParquetPrimitiveDataTypes()
+        {
+            string pathData = GetDataPath(@"..\data\Parquet", "alltypes.parquet");
+            TestCore(pathData, false, new[] { "loader=Parquet{bigIntDates=+}" });
+            Done();
+        }
+
+        [Fact]
+        public void TestParquetNull()
+        {
+            string pathData = GetDataPath(@"..\data\Parquet", "test-null.parquet");
+            TestCore(pathData, false, new[] { "loader=Parquet{bigIntDates=+}" }, forceDense: true);
+            Done();
+        }
+    }
 }
diff --git a/test/Microsoft.ML.TestFramework/Microsoft.ML.TestFramework.csproj b/test/Microsoft.ML.TestFramework/Microsoft.ML.TestFramework.csproj
index a80b2df83e..454d1d7a31 100644
--- a/test/Microsoft.ML.TestFramework/Microsoft.ML.TestFramework.csproj
+++ b/test/Microsoft.ML.TestFramework/Microsoft.ML.TestFramework.csproj
@@ -9,6 +9,7 @@
     <ProjectReference Include="..\..\src\Microsoft.ML.Data\Microsoft.ML.Data.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML.FastTree\Microsoft.ML.FastTree.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML.Maml\Microsoft.ML.Maml.csproj" />
+    <ProjectReference Include="..\..\src\Microsoft.ML.Parquet\Microsoft.ML.Parquet.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML.ResultProcessor\Microsoft.ML.ResultProcessor.csproj" />
     <ProjectReference Include="..\..\src\Microsoft.ML\Microsoft.ML.csproj" />
   </ItemGroup>
diff --git a/test/Microsoft.ML.TestFramework/TestInitialization.cs b/test/Microsoft.ML.TestFramework/TestInitialization.cs
index ebe0eb0a79..50d54c9f21 100644
--- a/test/Microsoft.ML.TestFramework/TestInitialization.cs
+++ b/test/Microsoft.ML.TestFramework/TestInitialization.cs
@@ -2,6 +2,7 @@
 // The .NET Foundation licenses this file to you under the MIT license.
 // See the LICENSE file in the project root for more information.
 
+using Xunit;
 using Xunit.Abstractions;
 
 namespace Microsoft.ML.Runtime.RunTests
diff --git a/test/data/Parquet/alltypes.parquet b/test/data/Parquet/alltypes.parquet
new file mode 100644
index 0000000000000000000000000000000000000000..e47e6b6e5587d5fb458fee85eab343b29e55af16
GIT binary patch
literal 1419
zcmaKsPe>GD6u_V3=kB_RDfNcg8ft@PDYI?cU16aPnpR4twn+yKnNg=QT>tG@2ZIRG
zFfBre5W-WGMG^D|%#&G!9y*kj<sl5KLr78(Aqw{9&*~n=_OkQl_j~XAzV|(*q9D2(
z0kbfii;Nx|=m6N<;{yH1psrq)WmXG)L*Z=w9T@?vvR5PF9n!`A3tNJP*T0O^EOZ}T
z6ojkly&yp8%S)#PGdqH%_Sv<xkW%mLE4Vv8zkhp|>vlH4Omt8*)AF(6KWSfC-}Cur
zcm3T`_p32+9Rwavp7olE9Ol?30$iEn-lmvV7DjBXJssa~OneHRzX|UK$|b7-`B-Ty
z*U6Cj=FcOn?hpkzzv{>M(}Q!Vf&io5)+5$#ytvmkwIk5qnZh>Q`ZyAXzijDsmboo2
z7TfA|vV3ZA?6*dj(-N83Fztf%*N&H4NepxClTM_7)Y%{7%-XAI3kyz&ghnbY&4mHm
zYSq6czwLte?twyP)>}>Nk*8iTxO3lm*%AYoZ(H$@BFn`Eqf1Lm51k4W{fs;?Muzh&
zt}VtErLDDH)ppi5YfbbQuREp26chnD2?VaBo(7j5(kmNcYFtxdEr1ykCpZtQ@wjqQ
zm1uDFm=!6SLNlzZCGjG)QPosRby4gnh&8u2X@HsNMG)3hHfu_w`A%}<RxAZ%q&W+9
zOKk&m>yar0&26v)jmk-hH-j`i2uhohqLAcGio%khFDB4phMOnl0M9(4XV&Kuk@Ms^
zT;S1<hKy%?kU!?5@$=P)=&;brVGSe7pYzp_F_j`>hNUFVZwOU<6G1Y@xD~_bh=FVQ
zHX?+FQ$>Wt8p~ZWoUME*VRE{dh%U>qI%fz$zKR$L(<EeCLUJ#yrOuE*)`v6^Sz@nN
zXANT?Uqg_LCk_$a3B&5PWt=8R#(;CBTgD9-*vFR<Av~Le%{y7<vpOG6YPP{c2G8N6
zgoyX1uaq}<c$xR66aP#+aZvLf4Ibrd2?6j!Zl1xmjTPqn`pZ<!dq!=GH#9eScl(3>
OkUtDF)b$Gb4F3ax_YjN#

literal 0
HcmV?d00001

diff --git a/test/data/Parquet/test-null.parquet b/test/data/Parquet/test-null.parquet
new file mode 100644
index 0000000000000000000000000000000000000000..a4c8a943b312b4b0d238e5b4dac44accbe799e04
GIT binary patch
literal 349
zcmZXQu};G<6h)oHR1p$P*s>)L9v}j#iDJbu8M?4BRvj1^knF~lQUwgA<;(apegHdk
zh{WKl>-Wy{yYl*BBM?9g@g;)6EKtq}OaK6Xih~1}G7Xw#u^dm}t`M0I#6E#hag_7x
zX&{M;Qo4GC-nj#U;c}CbZ0Fp`8SMdvl+k68vp}{vSkMVTDTeq3n<8KR%Tw%UY<OZ~
zpYU_B4{Y2yi-Nxs3;|{2qW8l%R$tbC4(^SdiR!+p0olB3|8ca3^40TGkBh3SL^<)L
uulcPx4r9-iQFW`O)pcu>vO+7f>txfkjW$~&yGClcwS9L7enNzG_}E|F7&hPl

literal 0
HcmV?d00001


From b0568ca15f60f4224f50d2db2f1108a87802be73 Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Tue, 28 Aug 2018 12:59:05 -0700
Subject: [PATCH 10/13] fix build.

---
 test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
index ba0749318b..314bff1b77 100644
--- a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
+++ b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
@@ -152,7 +152,7 @@ public sealed partial class TestDataPipe : TestDataPipeBase
         [Fact]
         public void TestParquetPrimitiveDataTypes()
         {
-            string pathData = GetDataPath(@"..\data\Parquet", "alltypes.parquet");
+            string pathData = GetDataPath(@"Parquet", "alltypes.parquet");
             TestCore(pathData, false, new[] { "loader=Parquet{bigIntDates=+}" });
             Done();
         }
@@ -160,7 +160,7 @@ public void TestParquetPrimitiveDataTypes()
         [Fact]
         public void TestParquetNull()
         {
-            string pathData = GetDataPath(@"..\data\Parquet", "test-null.parquet");
+            string pathData = GetDataPath(@"Parquet", "test-null.parquet");
             TestCore(pathData, false, new[] { "loader=Parquet{bigIntDates=+}" }, forceDense: true);
             Done();
         }

From 924cb8aba874f7077089cfa93c9ffe2daa3381bf Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Thu, 30 Aug 2018 20:19:41 -0700
Subject: [PATCH 11/13] misc.

---
 src/Microsoft.ML.Data/Data/Conversion.cs             | 12 +++++-------
 .../DataPipe/TestDataPipeBase.cs                     |  4 ++--
 2 files changed, 7 insertions(+), 9 deletions(-)

diff --git a/src/Microsoft.ML.Data/Data/Conversion.cs b/src/Microsoft.ML.Data/Data/Conversion.cs
index ec2bc2f977..0d0679c912 100644
--- a/src/Microsoft.ML.Data/Data/Conversion.cs
+++ b/src/Microsoft.ML.Data/Data/Conversion.cs
@@ -1612,12 +1612,9 @@ private U8 ParseU8(ref TX span)
         /// </summary>
         public bool TryParse(ref TX src, out BL dst)
         {
-            // NA text -> default.
-            if (src.IsNA)
-            {
-                dst = default;
-                return true;
-            }
+            // NA text -> Exception.
+            Contracts.Check(!src.IsNA, "Missing text values cannot be converted to bool value.");
+            Contracts.Check(!IsStdMissing(ref src), "Missing text values cannot be converted to bool value.");
 
             char ch;
             switch (src.Length)
@@ -1721,7 +1718,7 @@ public bool TryParse(ref TX src, out BL dst)
             }
 
             dst = false;
-            return IsStdMissing(ref src);
+            return false;
         }
 
         private bool TryParse(ref TX src, out TX dst)
@@ -1787,6 +1784,7 @@ public void Convert(ref TX span, ref TX value)
         }
         public void Convert(ref TX span, ref BL value)
         {
+            Contracts.Check(!span.IsNA, "Missing text values cannot be converted to bool value.");
             // When TryParseBL returns false, it should have set value to false.
             if (!TryParse(ref span, out value))
                 Contracts.Assert(!value);
diff --git a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs
index d189e627f5..b63d38b586 100644
--- a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs
+++ b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipeBase.cs
@@ -1008,7 +1008,7 @@ protected Func<bool> GetColumnComparer(IRow r1, IRow r2, int col, ColumnType typ
                     case DataKind.Text:
                         return GetComparerOne<DvText>(r1, r2, col, DvText.Identical);
                     case DataKind.Bool:
-                        return GetComparerOne<DvBool>(r1, r2, col, (x, y) => x.Equals(y));
+                        return GetComparerOne<bool>(r1, r2, col, (x, y) => x == y);
                     case DataKind.TimeSpan:
                         return GetComparerOne<DvTimeSpan>(r1, r2, col, (x, y) => x.Equals(y));
                     case DataKind.DT:
@@ -1054,7 +1054,7 @@ protected Func<bool> GetColumnComparer(IRow r1, IRow r2, int col, ColumnType typ
                     case DataKind.Text:
                         return GetComparerVec<DvText>(r1, r2, col, size, DvText.Identical);
                     case DataKind.Bool:
-                        return GetComparerVec<DvBool>(r1, r2, col, size, (x, y) => x.Equals(y));
+                        return GetComparerVec<bool>(r1, r2, col, size, (x, y) => x == y);
                     case DataKind.TimeSpan:
                         return GetComparerVec<DvTimeSpan>(r1, r2, col, size, (x, y) => x.Equals(y));
                     case DataKind.DT:

From 1b7209995a11dd30f0b1885bea70bdd4ccfb6dc2 Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Mon, 3 Sep 2018 17:32:48 -0700
Subject: [PATCH 12/13] merge parquet test.

---
 .../TestParquetPrimitiveDataTypes-Data.txt    | 28 ++++++++-----------
 .../TestParquetPrimitiveDataTypes-Schema.txt  | 24 ++++++----------
 .../TestParquetPrimitiveDataTypes-Data.txt    | 28 ++++++++-----------
 .../TestParquetPrimitiveDataTypes-Schema.txt  | 24 ++++++----------
 .../DataPipe/TestDataPipe.cs                  | 20 -------------
 5 files changed, 40 insertions(+), 84 deletions(-)

diff --git a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
index bbdd0c18ab..af1e19e1cc 100644
--- a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
+++ b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
@@ -1,21 +1,15 @@
 #@ TextLoader{
 #@   header+
 #@   sep=tab
-#@   col=Id:I4:0
-#@   col=Timestamp:DZ:1
-#@   col=Message:TX:2
-#@   col=Data:TX:3
-#@   col=IsDeleted:BL:4
-#@   col=Amount:R4:5
-#@   col=TotalAmount:R8:6
-#@   col=Counter:I8:7
-#@   col=Amount2:R8:8
-#@   col=Flag:U1:9
-#@   col=Flag2:I1:10
-#@   col=Flag3:I2:11
-#@   col=Flag4:U2:12
-#@   col=Flag5:TS:13
+#@   col=sbyte:I1:0
+#@   col=short:I2:1
+#@   col=int:I4:2
+#@   col=long:I8:3
+#@   col=bool:BL:4
+#@   col=DateTimeOffset:DZ:5
+#@   col=Interval:TS:6
+#@   col=string:TX:7
 #@ }
-Id	Timestamp	Message	Data	IsDeleted	Amount	TotalAmount	Counter	Amount2	Flag	Flag2	Flag3	Flag4	Flag5
-1	"2000-01-01T01:01:01.0000000+00:00"	Record1	SomeData3	0	125.4	400	300000	3331313	3	-3	-600	600	"3100.00:00:00.1000000"
-1	"2000-12-31T23:59:59.9990000+00:00"	Record2	SomeData4	0	126.4	500	400000	4331313	4	-4	-700	700	
+sbyte	short	int	long	bool	DateTimeOffset	Interval	string
+				1	"2018-09-01T19:53:18.2910000+00:00"	"31.00:00:00.0010000"	""
+127	32767	2147483647	9223372036854775807	0	"2018-09-01T19:53:18.3110000+00:00"	"31.00:00:00.0010000"	""""""
diff --git a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
index 213ef605e6..505df9d958 100644
--- a/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
+++ b/test/BaselineOutput/SingleDebug/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
@@ -1,16 +1,10 @@
 ---- ParquetLoader ----
-14 columns:
-  Id: I4
-  Timestamp: DateTimeZone
-  Message: Text
-  Data: Text
-  IsDeleted: Bool
-  Amount: R4
-  TotalAmount: R8
-  Counter: I8
-  Amount2: R8
-  Flag: U1
-  Flag2: I1
-  Flag3: I2
-  Flag4: U2
-  Flag5: TimeSpan
+8 columns:
+  sbyte: I1
+  short: I2
+  int: I4
+  long: I8
+  bool: Bool
+  DateTimeOffset: DateTimeZone
+  Interval: TimeSpan
+  string: Text
diff --git a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
index bbdd0c18ab..af1e19e1cc 100644
--- a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
+++ b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Data.txt
@@ -1,21 +1,15 @@
 #@ TextLoader{
 #@   header+
 #@   sep=tab
-#@   col=Id:I4:0
-#@   col=Timestamp:DZ:1
-#@   col=Message:TX:2
-#@   col=Data:TX:3
-#@   col=IsDeleted:BL:4
-#@   col=Amount:R4:5
-#@   col=TotalAmount:R8:6
-#@   col=Counter:I8:7
-#@   col=Amount2:R8:8
-#@   col=Flag:U1:9
-#@   col=Flag2:I1:10
-#@   col=Flag3:I2:11
-#@   col=Flag4:U2:12
-#@   col=Flag5:TS:13
+#@   col=sbyte:I1:0
+#@   col=short:I2:1
+#@   col=int:I4:2
+#@   col=long:I8:3
+#@   col=bool:BL:4
+#@   col=DateTimeOffset:DZ:5
+#@   col=Interval:TS:6
+#@   col=string:TX:7
 #@ }
-Id	Timestamp	Message	Data	IsDeleted	Amount	TotalAmount	Counter	Amount2	Flag	Flag2	Flag3	Flag4	Flag5
-1	"2000-01-01T01:01:01.0000000+00:00"	Record1	SomeData3	0	125.4	400	300000	3331313	3	-3	-600	600	"3100.00:00:00.1000000"
-1	"2000-12-31T23:59:59.9990000+00:00"	Record2	SomeData4	0	126.4	500	400000	4331313	4	-4	-700	700	
+sbyte	short	int	long	bool	DateTimeOffset	Interval	string
+				1	"2018-09-01T19:53:18.2910000+00:00"	"31.00:00:00.0010000"	""
+127	32767	2147483647	9223372036854775807	0	"2018-09-01T19:53:18.3110000+00:00"	"31.00:00:00.0010000"	""""""
diff --git a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
index 213ef605e6..505df9d958 100644
--- a/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
+++ b/test/BaselineOutput/SingleRelease/SavePipe/TestParquetPrimitiveDataTypes-Schema.txt
@@ -1,16 +1,10 @@
 ---- ParquetLoader ----
-14 columns:
-  Id: I4
-  Timestamp: DateTimeZone
-  Message: Text
-  Data: Text
-  IsDeleted: Bool
-  Amount: R4
-  TotalAmount: R8
-  Counter: I8
-  Amount2: R8
-  Flag: U1
-  Flag2: I1
-  Flag3: I2
-  Flag4: U2
-  Flag5: TimeSpan
+8 columns:
+  sbyte: I1
+  short: I2
+  int: I4
+  long: I8
+  bool: Bool
+  DateTimeOffset: DateTimeZone
+  Interval: TimeSpan
+  string: Text
diff --git a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
index 4fa03376d2..3abff3e560 100644
--- a/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
+++ b/test/Microsoft.ML.TestFramework/DataPipe/TestDataPipe.cs
@@ -243,24 +243,4 @@ public void TestLdaTransformEmptyDocumentException()
             Assert.True(false, "The LDA transform does not throw expected error on empty documents.");
         }
     }
-
-    public sealed partial class TestDataPipe : TestDataPipeBase
-    {
-
-        [Fact]
-        public void TestParquetPrimitiveDataTypes()
-        {
-            string pathData = GetDataPath(@"Parquet", "alltypes.parquet");
-            TestCore(pathData, false, new[] { "loader=Parquet{bigIntDates=+}" });
-            Done();
-        }
-
-        [Fact]
-        public void TestParquetNull()
-        {
-            string pathData = GetDataPath(@"Parquet", "test-null.parquet");
-            TestCore(pathData, false, new[] { "loader=Parquet{bigIntDates=+}" }, forceDense: true);
-            Done();
-        }
-    }
 }

From ffc1f8b67b582ccdeb98e41bec8289807cedcd61 Mon Sep 17 00:00:00 2001
From: Zeeshan Siddiqui <mzs@microsoft.com>
Date: Fri, 7 Sep 2018 11:54:03 -0700
Subject: [PATCH 13/13] merge master.

---
 src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs      | 6 +++---
 src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs         | 1 -
 src/Microsoft.ML.Data/Transforms/Normalizer.cs             | 4 ++--
 test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs | 6 +++---
 4 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs b/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs
index 39cc6cd316..ee3be8ba08 100644
--- a/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs
+++ b/src/Microsoft.ML.Data/StaticPipe/StaticSchemaShape.cs
@@ -254,9 +254,9 @@ private static Type GetTypeOrNull(IColumn col)
                         var normtype = meta.Schema.GetColumnType(normcol);
                         if (normtype == BoolType.Instance)
                         {
-                            DvBool val = default;
-                            meta.GetGetter<DvBool>(normcol)(ref val);
-                            if (val.IsTrue)
+                            bool val = default;
+                            meta.GetGetter<bool>(normcol)(ref val);
+                            if (val)
                                 vecType = typeof(NormVector<>);
                         }
                     }
diff --git a/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs b/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs
index ab79ab4e11..4cb4a2892f 100644
--- a/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs
+++ b/src/Microsoft.ML.Data/Transforms/NormalizeUtils.cs
@@ -146,7 +146,6 @@ public static CommonOutputs.TransformOutput Bin(IHostEnvironment env, NormalizeT
             EntryPointNode node)
         {
             var schema = input.Data.Schema;
-            DvBool isNormalized = DvBool.False;
             var columnsToNormalize = new List<NormalizeTransform.AffineColumn>();
             foreach (var column in input.Column)
             {
diff --git a/src/Microsoft.ML.Data/Transforms/Normalizer.cs b/src/Microsoft.ML.Data/Transforms/Normalizer.cs
index b757d2e7f8..8dadb7274f 100644
--- a/src/Microsoft.ML.Data/Transforms/Normalizer.cs
+++ b/src/Microsoft.ML.Data/Transforms/Normalizer.cs
@@ -473,7 +473,7 @@ private ColumnMetadataInfo MakeMetadata(int iinfo)
             {
                 var colInfo = _parent._columns[iinfo];
                 var result = new ColumnMetadataInfo(colInfo.Output);
-                result.Add(MetadataUtils.Kinds.IsNormalized, new MetadataInfo<DvBool>(BoolType.Instance, IsNormalizedGetter));
+                result.Add(MetadataUtils.Kinds.IsNormalized, new MetadataInfo<bool>(BoolType.Instance, IsNormalizedGetter));
                 if (InputSchema.HasSlotNames(ColMapNewToOld[iinfo], colInfo.InputType.VectorSize))
                 {
                     MetadataUtils.MetadataGetter<VBuffer<DvText>> getter = (int col, ref VBuffer<DvText> slotNames) =>
@@ -485,7 +485,7 @@ private ColumnMetadataInfo MakeMetadata(int iinfo)
                 return result;
             }
 
-            private void IsNormalizedGetter(int col, ref DvBool dst)
+            private void IsNormalizedGetter(int col, ref bool dst)
             {
                 dst = true;
             }
diff --git a/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs b/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs
index 603d9dcd2f..7d75188193 100644
--- a/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs
+++ b/test/Microsoft.ML.StaticPipelineTesting/StaticPipeTests.cs
@@ -80,11 +80,11 @@ public void SimpleTextLoaderCopyColumnsTest()
             // Next actually inspect the data.
             using (var cursor = textData.GetRowCursor(c => true))
             {
-                var labelGetter = cursor.GetGetter<DvBool>(labelIdx);
+                var labelGetter = cursor.GetGetter<bool>(labelIdx);
                 var textGetter = cursor.GetGetter<DvText>(textIdx);
                 var numericFeaturesGetter = cursor.GetGetter<VBuffer<float>>(numericFeaturesIdx);
 
-                DvBool labelVal = default;
+                bool labelVal = default;
                 DvText textVal = default;
                 VBuffer<float> numVal = default;
 
@@ -94,7 +94,7 @@ void CheckValuesSame(bool bl, string tx, float v0, float v1, float v2)
                     textGetter(ref textVal);
                     numericFeaturesGetter(ref numVal);
 
-                    Assert.Equal((DvBool)bl, labelVal);
+                    Assert.Equal((bool)bl, labelVal);
                     Assert.Equal(new DvText(tx), textVal);
                     Assert.Equal(3, numVal.Length);
                     Assert.Equal(v0, numVal.GetItemOrDefault(0));