Removes the learning rate parameter from RandomForest as this paramet…

…er was not used by the base class. This fixes dotnet#2237
singlis · Feb 22, 2019 · 7f67015 · 7f67015
1 parent 412e1f9
commit 7f67015
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Showing 4 changed files with 8 additions and 17 deletions.
diff --git a/src/Microsoft.ML.FastTree/RandomForest.cs b/src/Microsoft.ML.FastTree/RandomForest.cs
@@ -31,7 +31,6 @@ private protected RandomForestTrainerBase(IHostEnvironment env,
             int numLeaves,
             int numTrees,
             int minDatapointsInLeaves,
-            double learningRate,
             bool quantileEnabled = false)
             : base(env, label, featureColumn, weightColumn, null, numLeaves, numTrees, minDatapointsInLeaves)
         {

diff --git a/src/Microsoft.ML.FastTree/RandomForestClassification.cs b/src/Microsoft.ML.FastTree/RandomForestClassification.cs
@@ -143,16 +143,14 @@ public sealed class Options : FastForestOptionsBase
         /// <param name="numLeaves">The max number of leaves in each regression tree.</param>
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="minDatapointsInLeaves">The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data.</param>
-        /// <param name="learningRate">The learning rate.</param>
         internal FastForestClassification(IHostEnvironment env,
             string labelColumn = DefaultColumnNames.Label,
             string featureColumn = DefaultColumnNames.Features,
             string weightColumn = null,
             int numLeaves = Defaults.NumLeaves,
             int numTrees = Defaults.NumTrees,
-            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves,
-            double learningRate = Defaults.LearningRates)
-            : base(env, TrainerUtils.MakeBoolScalarLabel(labelColumn), featureColumn, weightColumn, null, numLeaves, numTrees, minDatapointsInLeaves, learningRate)
+            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves)
+            : base(env, TrainerUtils.MakeBoolScalarLabel(labelColumn), featureColumn, weightColumn, null, numLeaves, numTrees, minDatapointsInLeaves)
         {
             Host.CheckNonEmpty(labelColumn, nameof(labelColumn));
             Host.CheckNonEmpty(featureColumn, nameof(featureColumn));

diff --git a/src/Microsoft.ML.FastTree/RandomForestRegression.cs b/src/Microsoft.ML.FastTree/RandomForestRegression.cs
@@ -271,16 +271,14 @@ public sealed class Options : FastForestOptionsBase
         /// <param name="numLeaves">The max number of leaves in each regression tree.</param>
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="minDatapointsInLeaves">The minimal number of documents allowed in a leaf of a regression tree, out of the subsampled data.</param>
-        /// <param name="learningRate">The learning rate.</param>
         internal FastForestRegression(IHostEnvironment env,
             string labelColumn = DefaultColumnNames.Label,
             string featureColumn = DefaultColumnNames.Features,
             string weightColumn = null,
             int numLeaves = Defaults.NumLeaves,
             int numTrees = Defaults.NumTrees,
-            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves,
-            double learningRate = Defaults.LearningRates)
-            : base(env, TrainerUtils.MakeR4ScalarColumn(labelColumn), featureColumn, weightColumn, null, numLeaves, numTrees, minDatapointsInLeaves, learningRate)
+            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves)
+            : base(env, TrainerUtils.MakeR4ScalarColumn(labelColumn), featureColumn, weightColumn, null, numLeaves, numTrees, minDatapointsInLeaves)
         {
             Host.CheckNonEmpty(labelColumn, nameof(labelColumn));
             Host.CheckNonEmpty(featureColumn, nameof(featureColumn));

diff --git a/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs b/src/Microsoft.ML.FastTree/TreeTrainersCatalog.cs
@@ -257,19 +257,17 @@ public static FastTreeTweedieTrainer FastTreeTweedie(this RegressionCatalog.Regr
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="numLeaves">The maximum number of leaves per decision tree.</param>
         /// <param name="minDatapointsInLeaves">The minimal number of datapoints allowed in a leaf of the tree, out of the subsampled data.</param>
-        /// <param name="learningRate">The learning rate.</param>
         public static FastForestRegression FastForest(this RegressionCatalog.RegressionTrainers catalog,
             string labelColumn = DefaultColumnNames.Label,
             string featureColumn = DefaultColumnNames.Features,
             string weights = null,
             int numLeaves = Defaults.NumLeaves,
             int numTrees = Defaults.NumTrees,
-            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves,
-            double learningRate = Defaults.LearningRates)
+            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves)
         {
             Contracts.CheckValue(catalog, nameof(catalog));
             var env = CatalogUtils.GetEnvironment(catalog);
-            return new FastForestRegression(env, labelColumn, featureColumn, weights, numLeaves, numTrees, minDatapointsInLeaves, learningRate);
+            return new FastForestRegression(env, labelColumn, featureColumn, weights, numLeaves, numTrees, minDatapointsInLeaves);
         }
 
         /// <summary>
@@ -297,19 +295,17 @@ public static FastForestRegression FastForest(this RegressionCatalog.RegressionT
         /// <param name="numTrees">Total number of decision trees to create in the ensemble.</param>
         /// <param name="numLeaves">The maximum number of leaves per decision tree.</param>
         /// <param name="minDatapointsInLeaves">The minimal number of datapoints allowed in a leaf of the tree, out of the subsampled data.</param>
-        /// <param name="learningRate">The learning rate.</param>
         public static FastForestClassification FastForest(this BinaryClassificationCatalog.BinaryClassificationTrainers catalog,
             string labelColumn = DefaultColumnNames.Label,
             string featureColumn = DefaultColumnNames.Features,
             string weights = null,
             int numLeaves = Defaults.NumLeaves,
             int numTrees = Defaults.NumTrees,
-            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves,
-            double learningRate = Defaults.LearningRates)
+            int minDatapointsInLeaves = Defaults.MinDocumentsInLeaves)
         {
             Contracts.CheckValue(catalog, nameof(catalog));
             var env = CatalogUtils.GetEnvironment(catalog);
-            return new FastForestClassification(env, labelColumn, featureColumn, weights,numLeaves, numTrees, minDatapointsInLeaves, learningRate);
+            return new FastForestClassification(env, labelColumn, featureColumn, weights,numLeaves, numTrees, minDatapointsInLeaves);
         }
 
         /// <summary>