Towards 2326: Microsoft.ML.Ensemble and Microsoft.ML.TimeSeries namespace rationalization (#2491)

* moving Microsoft.ML.TimeSeriesProcessing, and Microsoft.ML.TimeSeries to Microsoft.ML.Transforms.TimeSeries

* Microsoft.ML.Ensemble to Microsoft.ML.Trainers.Ensemble

Author: sfilipi

docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs

@@ -5,11 +5,9 @@
 using System;
 using System.Collections.Generic;
 using System.IO;
-using System.Linq;
 using Microsoft.ML.Core.Data;
 using Microsoft.ML.Data;
-using Microsoft.ML.TimeSeries;
-using Microsoft.ML.TimeSeriesProcessing;
+using Microsoft.ML.Transforms.TimeSeries;
 
 namespace Microsoft.ML.Samples.Dynamic
 {

docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs

@@ -1,11 +1,9 @@
 using System;
 using System.Collections.Generic;
 using System.IO;
-using System.Linq;
 using Microsoft.ML.Core.Data;
 using Microsoft.ML.Data;
-using Microsoft.ML.TimeSeries;
-using Microsoft.ML.TimeSeriesProcessing;
+using Microsoft.ML.Transforms.TimeSeries;
 
 namespace Microsoft.ML.Samples.Dynamic
 {

docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs

@@ -1,11 +1,9 @@
 using System;
 using System.Collections.Generic;
 using System.IO;
-using System.Linq;
 using Microsoft.ML.Core.Data;
 using Microsoft.ML.Data;
-using Microsoft.ML.TimeSeries;
-using Microsoft.ML.TimeSeriesProcessing;
+using Microsoft.ML.Transforms.TimeSeries;
 
 namespace Microsoft.ML.Samples.Dynamic
 {

docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs

@@ -1,11 +1,9 @@
 using System;
 using System.Collections.Generic;
 using System.IO;
-using System.Linq;
 using Microsoft.ML.Core.Data;
 using Microsoft.ML.Data;
-using Microsoft.ML.TimeSeries;
-using Microsoft.ML.TimeSeriesProcessing;
+using Microsoft.ML.Transforms.TimeSeries;
 
 namespace Microsoft.ML.Samples.Dynamic
 {

src/Microsoft.ML.Ensemble/Batch.cs

@@ -4,7 +4,7 @@
 
 using Microsoft.ML.Data;
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     internal sealed class Batch
     {

src/Microsoft.ML.Ensemble/EnsembleUtils.cs

@@ -7,7 +7,7 @@
 using Microsoft.ML.Data;
 using Microsoft.ML.Internal.Utilities;
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     internal static class EnsembleUtils
     {

src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs

@@ -10,14 +10,13 @@
 using Microsoft.ML;
 using Microsoft.ML.CommandLine;
 using Microsoft.ML.Data;
-using Microsoft.ML.Ensemble;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Internal.Utilities;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(void), typeof(EnsembleCreator), null, typeof(SignatureEntryPointModule), "CreateEnsemble")]
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     /// <summary>
     /// A component to combine given models into an ensemble model.

src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs

@@ -2,16 +2,15 @@
 // The .NET Foundation licenses this file to you under the MIT license.
 // See the LICENSE file in the project root for more information.
 
-using Microsoft.ML.Ensemble;
-using Microsoft.ML.Ensemble.Selector;
-using Microsoft.ML.Ensemble.Selector.DiversityMeasure;
 using Microsoft.ML.EntryPoints;
+using Microsoft.ML.Trainers.Ensemble;
+using Microsoft.ML.Trainers.Ensemble.DiversityMeasure;
 
 [assembly: EntryPointModule(typeof(DisagreementDiversityFactory))]
 [assembly: EntryPointModule(typeof(RegressionDisagreementDiversityFactory))]
 [assembly: EntryPointModule(typeof(MultiDisagreementDiversityFactory))]
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     [TlcModule.Component(Name = DisagreementDiversityMeasure.LoadName, FriendlyName = DisagreementDiversityMeasure.UserName)]
     internal sealed class DisagreementDiversityFactory : ISupportBinaryDiversityMeasureFactory

src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs

@@ -3,12 +3,12 @@
 // See the LICENSE file in the project root for more information.
 
 using Microsoft.ML;
-using Microsoft.ML.Ensemble;
 using Microsoft.ML.EntryPoints;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(void), typeof(Ensemble), null, typeof(SignatureEntryPointModule), "TrainEnsemble")]
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     internal static class Ensemble
     {

src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs

@@ -2,15 +2,14 @@
 // The .NET Foundation licenses this file to you under the MIT license.
 // See the LICENSE file in the project root for more information.
 
-using Microsoft.ML.Ensemble;
-using Microsoft.ML.Ensemble.Selector;
-using Microsoft.ML.Ensemble.Selector.FeatureSelector;
 using Microsoft.ML.EntryPoints;
+using Microsoft.ML.Trainers.Ensemble;
+using Microsoft.ML.Trainers.Ensemble.FeatureSelector;
 
 [assembly: EntryPointModule(typeof(AllFeatureSelectorFactory))]
 [assembly: EntryPointModule(typeof(RandomFeatureSelector))]
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     [TlcModule.Component(Name = AllFeatureSelector.LoadName, FriendlyName = AllFeatureSelector.UserName)]
     public sealed class AllFeatureSelectorFactory : ISupportFeatureSelectorFactory

src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs

@@ -2,9 +2,8 @@
 // The .NET Foundation licenses this file to you under the MIT license.
 // See the LICENSE file in the project root for more information.
 
-using Microsoft.ML.Ensemble;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.EntryPoints;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: EntryPointModule(typeof(AverageFactory))]
 [assembly: EntryPointModule(typeof(MedianFactory))]
@@ -18,7 +17,7 @@
 [assembly: EntryPointModule(typeof(VotingFactory))]
 [assembly: EntryPointModule(typeof(WeightedAverage))]
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     [TlcModule.Component(Name = Average.LoadName, FriendlyName = Average.UserName)]
     public sealed class AverageFactory : ISupportBinaryOutputCombinerFactory, ISupportRegressionOutputCombinerFactory

src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs

@@ -4,13 +4,13 @@
 
 using Microsoft.Data.DataView;
 using Microsoft.ML.Data;
-using Microsoft.ML.Ensemble;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Internal.Calibration;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: EntryPointModule(typeof(PipelineEnsemble))]
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     internal static class PipelineEnsemble
     {

src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs

@@ -2,10 +2,9 @@
 // The .NET Foundation licenses this file to you under the MIT license.
 // See the LICENSE file in the project root for more information.
 
-using Microsoft.ML.Ensemble;
-using Microsoft.ML.Ensemble.Selector;
-using Microsoft.ML.Ensemble.Selector.SubModelSelector;
 using Microsoft.ML.EntryPoints;
+using Microsoft.ML.Trainers.Ensemble;
+using Microsoft.ML.Trainers.Ensemble.SubModelSelector;
 
 [assembly: EntryPointModule(typeof(AllSelectorFactory))]
 [assembly: EntryPointModule(typeof(AllSelectorMultiClassFactory))]
@@ -16,7 +15,7 @@
 [assembly: EntryPointModule(typeof(BestPerformanceSelector))]
 [assembly: EntryPointModule(typeof(BestPerformanceSelectorMultiClass))]
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     [TlcModule.Component(Name = AllSelector.LoadName, FriendlyName = AllSelector.UserName)]
     public sealed class AllSelectorFactory : ISupportBinarySubModelSelectorFactory, ISupportRegressionSubModelSelectorFactory

src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs

@@ -6,7 +6,7 @@
 using System.Collections.Generic;
 using Microsoft.ML.Internal.Utilities;
 
-namespace Microsoft.ML.Ensemble
+namespace Microsoft.ML.Trainers.Ensemble
 {
     internal sealed class FeatureSubsetModel<TOutput>
     {

src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs

@@ -4,13 +4,13 @@
 
 using System;
 using Microsoft.ML;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.Model;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(Average), null, typeof(SignatureCombiner), Average.UserName)]
 [assembly: LoadableClass(typeof(Average), null, typeof(SignatureLoadModel), Average.UserName, Average.LoaderSignature)]
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     public sealed class Average : BaseAverager, IRegressionOutputCombiner
     {

src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs

@@ -5,7 +5,7 @@
 using System;
 using Microsoft.ML.Model;
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     public abstract class BaseAverager : IBinaryOutputCombiner, ICanSaveModel
     {

src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs

@@ -8,7 +8,7 @@
 using Microsoft.ML.Model;
 using Microsoft.ML.Numeric;
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     public abstract class BaseMultiAverager : BaseMultiCombiner
     {

src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs

@@ -9,7 +9,7 @@
 using Microsoft.ML.Model;
 using Microsoft.ML.Numeric;
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     public abstract class BaseMultiCombiner : IMultiClassOutputCombiner, ICanSaveModel
     {

src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs

@@ -7,7 +7,7 @@
 using Microsoft.ML.Internal.Utilities;
 using Microsoft.ML.Model;
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     internal abstract class BaseScalarStacking : BaseStacking<Single>
     {

src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs

@@ -13,7 +13,7 @@
 using Microsoft.ML.Model;
 using Microsoft.ML.Training;
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     internal abstract class BaseStacking<TOutput> : IStackingTrainer<TOutput>, ICanSaveModel
     {

src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs

@@ -7,7 +7,7 @@
 using Microsoft.ML.Data;
 using Microsoft.ML.EntryPoints;
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     /// <summary>
     /// Signature for combiners.

src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs

@@ -4,14 +4,14 @@
 
 using System;
 using Microsoft.ML;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.Internal.Utilities;
 using Microsoft.ML.Model;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(Median), null, typeof(SignatureCombiner), Median.UserName, Median.LoadName)]
 [assembly: LoadableClass(typeof(Median), null, typeof(SignatureLoadModel), Median.UserName, Median.LoaderSignature)]
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     /// <summary>
     /// Generic interface for combining outputs of multiple models

src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs

@@ -5,16 +5,16 @@
 using System;
 using Microsoft.ML;
 using Microsoft.ML.Data;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Model;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(MultiAverage), typeof(MultiAverage.Arguments), typeof(SignatureCombiner),
     Average.UserName, MultiAverage.LoadName)]
 [assembly: LoadableClass(typeof(MultiAverage), null, typeof(SignatureLoadModel), Average.UserName,
     MultiAverage.LoadName, MultiAverage.LoaderSignature)]
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     public sealed class MultiAverage : BaseMultiAverager
     {

src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs

@@ -5,16 +5,16 @@
 using System;
 using Microsoft.ML;
 using Microsoft.ML.Data;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Internal.Utilities;
 using Microsoft.ML.Model;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(MultiMedian), typeof(MultiMedian.Arguments), typeof(SignatureCombiner),
     Median.UserName, MultiMedian.LoadName)]
 [assembly: LoadableClass(typeof(MultiMedian), null, typeof(SignatureLoadModel), Median.UserName, MultiMedian.LoaderSignature)]
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     /// <summary>
     /// Generic interface for combining outputs of multiple models

src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs

@@ -6,18 +6,18 @@
 using Microsoft.ML;
 using Microsoft.ML.CommandLine;
 using Microsoft.ML.Data;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Internal.Internallearn;
 using Microsoft.ML.Model;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(MultiStacking), typeof(MultiStacking.Arguments), typeof(SignatureCombiner),
    Stacking.UserName, MultiStacking.LoadName)]
 
 [assembly: LoadableClass(typeof(MultiStacking), null, typeof(SignatureLoadModel),
     Stacking.UserName, MultiStacking.LoaderSignature)]
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     using TVectorPredictor = IPredictorProducing<VBuffer<Single>>;
     internal sealed class MultiStacking : BaseStacking<VBuffer<Single>>, IMultiClassOutputCombiner

src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs

@@ -5,15 +5,15 @@
 using System;
 using Microsoft.ML;
 using Microsoft.ML.Data;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.Internal.Utilities;
 using Microsoft.ML.Model;
 using Microsoft.ML.Numeric;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(MultiVoting), null, typeof(SignatureCombiner), Voting.UserName, MultiVoting.LoadName)]
 [assembly: LoadableClass(typeof(MultiVoting), null, typeof(SignatureLoadModel), Voting.UserName, MultiVoting.LoaderSignature)]
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     // REVIEW: Why is MultiVoting based on BaseMultiCombiner? Normalizing the model outputs
     // is senseless, so the base adds no real functionality.

src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs

@@ -6,18 +6,18 @@
 using Microsoft.ML;
 using Microsoft.ML.CommandLine;
 using Microsoft.ML.Data;
-using Microsoft.ML.Ensemble.OutputCombiners;
 using Microsoft.ML.EntryPoints;
 using Microsoft.ML.Internal.Internallearn;
 using Microsoft.ML.Model;
+using Microsoft.ML.Trainers.Ensemble;
 
 [assembly: LoadableClass(typeof(MultiWeightedAverage), typeof(MultiWeightedAverage.Arguments), typeof(SignatureCombiner),
     MultiWeightedAverage.UserName, MultiWeightedAverage.LoadName)]
 
 [assembly: LoadableClass(typeof(MultiWeightedAverage), null, typeof(SignatureLoadModel),
     MultiWeightedAverage.UserName, MultiWeightedAverage.LoaderSignature)]
 
-namespace Microsoft.ML.Ensemble.OutputCombiners
+namespace Microsoft.ML.Trainers.Ensemble
 {
     /// <summary>
     /// Generic interface for combining outputs of multiple models