rename 'AutoFitter' to 'Experiment' (dotnet#169)

src/Microsoft.ML.Auto/API/BinaryClassificationExperiment.cs

@@ -85,12 +85,12 @@ internal IEnumerable<RunResult<BinaryClassificationMetrics>> Execute(MLContext c
             //UserInputValidationUtil.ValidateAutoFitArgs(trainData, labelColunName, validationData, settings, columnPurposes)
 
             // run autofit & get all pipelines run in that process
-            var autoFitter = new AutoFitter<BinaryClassificationMetrics>(context, TaskKind.BinaryClassification, trainData, columnInfo, 
+            var experiment = new Experiment<BinaryClassificationMetrics>(context, TaskKind.BinaryClassification, trainData, columnInfo, 
                 validationData, preFeaturizers, new OptimizingMetricInfo(_settings.OptimizingMetric), _settings.ProgressCallback, 
                 _settings, new BinaryMetricsAgent(_settings.OptimizingMetric), 
                 TrainerExtensionUtil.GetTrainerNames(_settings.WhitelistedTrainers));
 
-            return autoFitter.Fit();
+            return experiment.Execute();
         }
     }
 

src/Microsoft.ML.Auto/API/MulticlassClassificationExperiment.cs

@@ -83,12 +83,12 @@ internal IEnumerable<RunResult<MultiClassClassifierMetrics>> Execute(MLContext c
             //UserInputValidationUtil.ValidateAutoFitArgs(trainData, labelColunName, validationData, settings, columnPurposes)
 
             // run autofit & get all pipelines run in that process
-            var autoFitter = new AutoFitter<MultiClassClassifierMetrics>(context, TaskKind.MulticlassClassification, trainData, 
+            var experiment = new Experiment<MultiClassClassifierMetrics>(context, TaskKind.MulticlassClassification, trainData, 
                 columnInfo, validationData, preFeaturizers, new OptimizingMetricInfo(_settings.OptimizingMetric),
                 _settings.ProgressCallback, _settings, new MultiMetricsAgent(_settings.OptimizingMetric),
                 TrainerExtensionUtil.GetTrainerNames(_settings.WhitelistedTrainers));
 
-            return autoFitter.Fit();
+            return experiment.Execute();
         }
     }
 

src/Microsoft.ML.Auto/API/RegressionExperiment.cs

@@ -80,12 +80,12 @@ internal IEnumerable<RunResult<RegressionMetrics>> Execute(MLContext context,
             //UserInputValidationUtil.ValidateAutoFitArgs(trainData, labelColunName, validationData, settings, columnPurposes);
 
             // run autofit & get all pipelines run in that process
-            var autoFitter = new AutoFitter<RegressionMetrics>(context, TaskKind.Regression, trainData, columnInfo, 
+            var experiment = new Experiment<RegressionMetrics>(context, TaskKind.Regression, trainData, columnInfo, 
                 validationData, preFeaturizers, new OptimizingMetricInfo(_settings.OptimizingMetric), 
                 _settings.ProgressCallback, _settings, new RegressionMetricsAgent(_settings.OptimizingMetric),
                 TrainerExtensionUtil.GetTrainerNames(_settings.WhitelistedTrainers));
 
-            return autoFitter.Fit();
+            return experiment.Execute();
         }
     }
 

src/Microsoft.ML.Auto/AutoFitter/AutoFitter.cs → src/Microsoft.ML.Auto/Experiment/Experiment.cs

@@ -11,7 +11,7 @@
 
 namespace Microsoft.ML.Auto
 {
-    internal class AutoFitter<T> where T : class
+    internal class Experiment<T> where T : class
     {
         private readonly IList<SuggestedPipelineResult<T>> _history;
         private readonly ColumnInformation _columnInfo;
@@ -29,7 +29,7 @@ internal class AutoFitter<T> where T : class
 
         List<RunResult<T>> iterationResults = new List<RunResult<T>>();
 
-        public AutoFitter(MLContext context,
+        public Experiment(MLContext context,
             TaskKind task,
             IDataView trainData,
             ColumnInformation columnInfo,
@@ -60,7 +60,7 @@ public AutoFitter(MLContext context,
             _trainerWhitelist = trainerWhitelist;
         }
 
-        public List<RunResult<T>> Fit()
+        public List<RunResult<T>> Execute()
         {
             ITransformer preprocessorTransform = null;
             if (_preFeaturizers != null)