diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs index d7dbc8553b..9b34510bd0 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/IidChangePointDetectorTransform.cs +++ b/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 { diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs index c03449be17..c2fedc5275 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/IidSpikeDetectorTransform.cs +++ b/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 { diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs index 19bb5e75c5..223bab2277 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaChangePointDetectorTransform.cs +++ b/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 { diff --git a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs b/docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs index 217ddb69ed..9ebf1a41d2 100644 --- a/docs/samples/Microsoft.ML.Samples/Dynamic/SsaSpikeDetectorTransform.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/Batch.cs b/src/Microsoft.ML.Ensemble/Batch.cs index caaf6bf4f3..756b095c72 100644 --- a/src/Microsoft.ML.Ensemble/Batch.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/EnsembleUtils.cs b/src/Microsoft.ML.Ensemble/EnsembleUtils.cs index 2af9b96f3b..342a33b9bd 100644 --- a/src/Microsoft.ML.Ensemble/EnsembleUtils.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs index baad8e2ca9..6ce5673797 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/CreateEnsemble.cs +++ b/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 { /// /// A component to combine given models into an ensemble model. diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs b/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs index 069cce2556..075b3659ec 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/DiversityMeasure.cs +++ b/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 diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs index 4aa0ab10ce..afec3af471 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/Ensemble.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs b/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs index 66ae78ecb5..8af31a0723 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/FeatureSelector.cs +++ b/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 diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs b/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs index da10f30de4..5af5cdf487 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/OutputCombiner.cs +++ b/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 diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs b/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs index 9452a9d064..2bafa85a2f 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/PipelineEnsemble.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs b/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs index b749501f76..867833f999 100644 --- a/src/Microsoft.ML.Ensemble/EntryPoints/SubModelSelector.cs +++ b/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 diff --git a/src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs b/src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs index 733573d39f..d583a1b125 100644 --- a/src/Microsoft.ML.Ensemble/FeatureSubsetModel.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs index 4582d4f4a9..e78e63cecc 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Average.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs index 0b454be238..1d8f56e3fe 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseAverager.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs index 73e6f4ea7e..044ccfb44e 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiAverager.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs index 737cbfd649..d0ee4583b3 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseMultiCombiner.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs index ba75e05080..59700cb18c 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseScalarStacking.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs index c081feee14..a172a6bce4 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/BaseStacking.cs +++ b/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 : IStackingTrainer, ICanSaveModel { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs index bbbbecf217..e054cd2fa8 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/IOutputCombiner.cs +++ b/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 { /// /// Signature for combiners. diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs index 5173216711..88a9d73ca3 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Median.cs +++ b/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 { /// /// Generic interface for combining outputs of multiple models diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs index be3bd7dfa2..3cf424b50f 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiAverage.cs +++ b/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 { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs index 94b0f38ae8..3b44413397 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiMedian.cs +++ b/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 { /// /// Generic interface for combining outputs of multiple models diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs index f2bb13d029..01011a99d4 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiStacking.cs @@ -6,10 +6,10 @@ 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)] @@ -17,7 +17,7 @@ [assembly: LoadableClass(typeof(MultiStacking), null, typeof(SignatureLoadModel), Stacking.UserName, MultiStacking.LoaderSignature)] -namespace Microsoft.ML.Ensemble.OutputCombiners +namespace Microsoft.ML.Trainers.Ensemble { using TVectorPredictor = IPredictorProducing>; internal sealed class MultiStacking : BaseStacking>, IMultiClassOutputCombiner diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs index a222606ae1..f943a4176c 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiVoting.cs +++ b/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. diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs index 161487650a..aecc3963bc 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/MultiWeightedAverage.cs @@ -6,10 +6,10 @@ 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)] @@ -17,7 +17,7 @@ [assembly: LoadableClass(typeof(MultiWeightedAverage), null, typeof(SignatureLoadModel), MultiWeightedAverage.UserName, MultiWeightedAverage.LoaderSignature)] -namespace Microsoft.ML.Ensemble.OutputCombiners +namespace Microsoft.ML.Trainers.Ensemble { /// /// Generic interface for combining outputs of multiple models diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs index 239e386ebf..ae9ef67db8 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/RegressionStacking.cs @@ -4,10 +4,10 @@ using System; using Microsoft.ML; using Microsoft.ML.CommandLine; -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(RegressionStacking), typeof(RegressionStacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, RegressionStacking.LoadName)] @@ -15,7 +15,7 @@ [assembly: LoadableClass(typeof(RegressionStacking), null, typeof(SignatureLoadModel), Stacking.UserName, RegressionStacking.LoaderSignature)] -namespace Microsoft.ML.Ensemble.OutputCombiners +namespace Microsoft.ML.Trainers.Ensemble { using TScalarPredictor = IPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs index 9999544c6c..93fe1d3240 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/Stacking.cs @@ -5,15 +5,15 @@ using System; using Microsoft.ML; using Microsoft.ML.CommandLine; -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(Stacking), typeof(Stacking.Arguments), typeof(SignatureCombiner), Stacking.UserName, Stacking.LoadName)] [assembly: LoadableClass(typeof(Stacking), null, typeof(SignatureLoadModel), Stacking.UserName, Stacking.LoaderSignature)] -namespace Microsoft.ML.Ensemble.OutputCombiners +namespace Microsoft.ML.Trainers.Ensemble { using TScalarPredictor = IPredictorProducing; internal sealed class Stacking : BaseScalarStacking, IBinaryOutputCombiner diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.cs index 3700782957..17c569d8ce 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/Voting.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(Voting), null, typeof(SignatureCombiner), Voting.UserName, Voting.LoadName)] [assembly: LoadableClass(typeof(Voting), null, typeof(SignatureLoadModel), Voting.UserName, Voting.LoaderSignature)] -namespace Microsoft.ML.Ensemble.OutputCombiners +namespace Microsoft.ML.Trainers.Ensemble { public sealed class Voting : IBinaryOutputCombiner, ICanSaveModel { diff --git a/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs b/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs index e6164b1914..e5aa458768 100644 --- a/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs +++ b/src/Microsoft.ML.Ensemble/OutputCombiners/WeightedAverage.cs @@ -6,10 +6,10 @@ 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(WeightedAverage), typeof(WeightedAverage.Arguments), typeof(SignatureCombiner), WeightedAverage.UserName, WeightedAverage.LoadName)] @@ -17,7 +17,7 @@ [assembly: LoadableClass(typeof(WeightedAverage), null, typeof(SignatureLoadModel), WeightedAverage.UserName, WeightedAverage.LoaderSignature)] -namespace Microsoft.ML.Ensemble.OutputCombiners +namespace Microsoft.ML.Trainers.Ensemble { public sealed class WeightedAverage : BaseAverager, IWeightedAverager { diff --git a/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs b/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs index 6f22df98c5..4f44a42204 100644 --- a/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs +++ b/src/Microsoft.ML.Ensemble/PipelineEnsemble.cs @@ -10,18 +10,17 @@ using Microsoft.Data.DataView; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Calibration; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; +using Microsoft.ML.Trainers.Ensemble; [assembly: LoadableClass(typeof(SchemaBindablePipelineEnsembleBase), null, typeof(SignatureLoadModel), SchemaBindablePipelineEnsembleBase.UserName, SchemaBindablePipelineEnsembleBase.LoaderSignature)] -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { /// /// This class represents an ensemble predictor, where each predictor has its own featurization pipeline. It is diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs index b4106a7b1d..c2f40e0b1a 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/BaseDisagreementDiversityMeasure.cs @@ -6,7 +6,7 @@ using System.Collections.Concurrent; using System.Collections.Generic; -namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Trainers.Ensemble.DiversityMeasure { internal abstract class BaseDisagreementDiversityMeasure : IDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs index bb0127003f..4cb1cbd883 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/DisagreementDiversityMeasure.cs @@ -4,13 +4,13 @@ using System; using Microsoft.ML; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; [assembly: LoadableClass(typeof(DisagreementDiversityMeasure), null, typeof(SignatureEnsembleDiversityMeasure), DisagreementDiversityMeasure.UserName, DisagreementDiversityMeasure.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Trainers.Ensemble.DiversityMeasure { internal sealed class DisagreementDiversityMeasure : BaseDisagreementDiversityMeasure, IBinaryDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs index b182ad9963..04c9e7f2d2 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/ModelDiversityMetric.cs @@ -4,7 +4,7 @@ using System; -namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Trainers.Ensemble.DiversityMeasure { internal sealed class ModelDiversityMetric { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs index ffb6839818..ccdd4d6b0b 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/MultiDisagreementDiversityMeasure.cs @@ -5,14 +5,14 @@ using System; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; using Microsoft.ML.Numeric; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; [assembly: LoadableClass(typeof(MultiDisagreementDiversityMeasure), null, typeof(SignatureEnsembleDiversityMeasure), DisagreementDiversityMeasure.UserName, MultiDisagreementDiversityMeasure.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Trainers.Ensemble.DiversityMeasure { internal sealed class MultiDisagreementDiversityMeasure : BaseDisagreementDiversityMeasure>, IMulticlassDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs index 2b60e44f1c..c1b37411b6 100644 --- a/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/DiversityMeasure/RegressionDisagreementDiversityMeasure.cs @@ -4,13 +4,13 @@ using System; using Microsoft.ML; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; [assembly: LoadableClass(typeof(RegressionDisagreementDiversityMeasure), null, typeof(SignatureEnsembleDiversityMeasure), DisagreementDiversityMeasure.UserName, RegressionDisagreementDiversityMeasure.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.DiversityMeasure +namespace Microsoft.ML.Trainers.Ensemble.DiversityMeasure { internal sealed class RegressionDisagreementDiversityMeasure : BaseDisagreementDiversityMeasure, IRegressionDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs index f2ffadf877..52c0a4752b 100644 --- a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/AllFeatureSelector.cs @@ -5,13 +5,13 @@ using System; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.FeatureSelector; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.FeatureSelector; [assembly: LoadableClass(typeof(AllFeatureSelector), null, typeof(SignatureEnsembleFeatureSelector), AllFeatureSelector.UserName, AllFeatureSelector.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.FeatureSelector +namespace Microsoft.ML.Trainers.Ensemble.FeatureSelector { internal sealed class AllFeatureSelector : IFeatureSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs index 93c4bd7603..5841d8c126 100644 --- a/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/FeatureSelector/RandomFeatureSelector.cs @@ -7,15 +7,15 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -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; using Microsoft.ML.Training; [assembly: LoadableClass(typeof(RandomFeatureSelector), typeof(RandomFeatureSelector.Arguments), typeof(SignatureEnsembleFeatureSelector), RandomFeatureSelector.UserName, RandomFeatureSelector.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.FeatureSelector +namespace Microsoft.ML.Trainers.Ensemble.FeatureSelector { internal class RandomFeatureSelector : IFeatureSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs b/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs index 8ac30f3818..96642ccc8f 100644 --- a/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs +++ b/src/Microsoft.ML.Ensemble/Selector/IDiversityMeasure.cs @@ -6,10 +6,10 @@ using System.Collections.Concurrent; using System.Collections.Generic; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; using Microsoft.ML.EntryPoints; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; -namespace Microsoft.ML.Ensemble.Selector +namespace Microsoft.ML.Trainers.Ensemble { internal interface IDiversityMeasure { diff --git a/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs b/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs index e4eb986294..6ccc6da5d7 100644 --- a/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/IFeatureSelector.cs @@ -6,7 +6,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Ensemble.Selector +namespace Microsoft.ML.Trainers.Ensemble { internal interface IFeatureSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs b/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs index e5b35082ee..6f910f6a44 100644 --- a/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/ISubModelSelector.cs @@ -7,7 +7,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Ensemble.Selector +namespace Microsoft.ML.Trainers.Ensemble { internal interface ISubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs b/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs index 6ba7002508..8ffef7aba1 100644 --- a/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/ISubsetSelector.cs @@ -7,7 +7,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; -namespace Microsoft.ML.Ensemble.Selector +namespace Microsoft.ML.Trainers.Ensemble { internal interface ISubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs index f88df3bfee..ce62ee9180 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelector.cs @@ -4,12 +4,12 @@ using System; using Microsoft.ML; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(AllSelector), null, typeof(SignatureEnsembleSubModelSelector), AllSelector.UserName, AllSelector.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class AllSelector : BaseSubModelSelector, IBinarySubModelSelector, IRegressionSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs index 2158b05733..6905579c3b 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/AllSelectorMultiClass.cs @@ -5,13 +5,13 @@ using System; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(AllSelectorMultiClass), null, typeof(SignatureEnsembleSubModelSelector), AllSelectorMultiClass.UserName, AllSelectorMultiClass.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class AllSelectorMultiClass : BaseSubModelSelector>, IMulticlassSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs index 55add475f5..a13ef47b35 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseBestPerformanceSelector.cs @@ -8,7 +8,7 @@ using System.Reflection; using Microsoft.ML.CommandLine; -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal abstract class BaseBestPerformanceSelector : SubModelDataSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs index e1edba726e..8f6d783c76 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseDiverseSelector.cs @@ -6,11 +6,11 @@ using System.Collections.Concurrent; using System.Collections.Generic; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; using Microsoft.ML.Training; -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal abstract class BaseDiverseSelector : SubModelDataSelector where TDiversityMetric : class, IDiversityMeasure diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs index 8d1189d049..87a61192cd 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BaseSubModelSelector.cs @@ -8,7 +8,7 @@ using Microsoft.Data.DataView; using Microsoft.ML.Data; -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal abstract class BaseSubModelSelector : ISubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs index 3b2204af4a..869da7307e 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorBinary.cs @@ -7,16 +7,16 @@ using System.Collections.Generic; using Microsoft.ML; using Microsoft.ML.CommandLine; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(BestDiverseSelectorBinary), typeof(BestDiverseSelectorBinary.Arguments), typeof(SignatureEnsembleSubModelSelector), BestDiverseSelectorBinary.UserName, BestDiverseSelectorBinary.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class BestDiverseSelectorBinary : BaseDiverseSelector, IBinarySubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs index 8bae59d1f5..9a39b4f5b3 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorMultiClass.cs @@ -8,16 +8,16 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(BestDiverseSelectorMultiClass), typeof(BestDiverseSelectorMultiClass.Arguments), typeof(SignatureEnsembleSubModelSelector), BestDiverseSelectorMultiClass.UserName, BestDiverseSelectorMultiClass.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class BestDiverseSelectorMultiClass : BaseDiverseSelector, IDiversityMeasure>>, IMulticlassSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs index 132f691034..2022e7d057 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestDiverseSelectorRegression.cs @@ -7,16 +7,16 @@ using System.Collections.Generic; using Microsoft.ML; using Microsoft.ML.CommandLine; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.DiversityMeasure; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.DiversityMeasure; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(BestDiverseSelectorRegression), typeof(BestDiverseSelectorRegression.Arguments), typeof(SignatureEnsembleSubModelSelector), BestDiverseSelectorRegression.UserName, BestDiverseSelectorRegression.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class BestDiverseSelectorRegression : BaseDiverseSelector, IRegressionSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs index be7b7e8f35..de6fe8874d 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceRegressionSelector.cs @@ -6,15 +6,15 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(BestPerformanceRegressionSelector), typeof(BestPerformanceRegressionSelector.Arguments), typeof(SignatureEnsembleSubModelSelector), BestPerformanceRegressionSelector.UserName, BestPerformanceRegressionSelector.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class BestPerformanceRegressionSelector : BaseBestPerformanceSelector, IRegressionSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs index 9b24798276..f11b30556f 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelector.cs @@ -6,15 +6,15 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(BestPerformanceSelector), typeof(BestPerformanceSelector.Arguments), typeof(SignatureEnsembleSubModelSelector), BestPerformanceSelector.UserName, BestPerformanceSelector.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class BestPerformanceSelector : BaseBestPerformanceSelector, IBinarySubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs index 36f9635c87..34ce8719db 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/BestPerformanceSelectorMultiClass.cs @@ -6,15 +6,15 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubModelSelector; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubModelSelector; [assembly: LoadableClass(typeof(BestPerformanceSelectorMultiClass), typeof(BestPerformanceSelectorMultiClass.Arguments), typeof(SignatureEnsembleSubModelSelector), BestPerformanceSelectorMultiClass.UserName, BestPerformanceSelectorMultiClass.LoadName)] -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal sealed class BestPerformanceSelectorMultiClass : BaseBestPerformanceSelector>, IMulticlassSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs index 0ba6497f25..ff8dd74354 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubModelSelector/SubModelDataSelector.cs @@ -6,7 +6,7 @@ using Microsoft.ML.CommandLine; using Microsoft.ML.Internal.Internallearn; -namespace Microsoft.ML.Ensemble.Selector.SubModelSelector +namespace Microsoft.ML.Trainers.Ensemble.SubModelSelector { internal abstract class SubModelDataSelector : BaseSubModelSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs index 43203e9ca9..1c1c15c3cd 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/AllInstanceSelector.cs @@ -5,16 +5,16 @@ using System; using System.Collections.Generic; using Microsoft.ML; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubsetSelector; using Microsoft.ML.EntryPoints; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubsetSelector; [assembly: LoadableClass(typeof(AllInstanceSelector), typeof(AllInstanceSelector.Arguments), typeof(SignatureEnsembleDataSelector), AllInstanceSelector.UserName, AllInstanceSelector.LoadName)] [assembly: EntryPointModule(typeof(AllInstanceSelector))] -namespace Microsoft.ML.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Trainers.Ensemble.SubsetSelector { internal sealed class AllInstanceSelector : BaseSubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs index 8504525012..3305574d36 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BaseSubsetSelector.cs @@ -8,7 +8,7 @@ using Microsoft.ML.Data; using Microsoft.ML.Transforms; -namespace Microsoft.ML.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Trainers.Ensemble.SubsetSelector { internal abstract class BaseSubsetSelector : ISubsetSelector where TArgs : BaseSubsetSelector.ArgumentsBase diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs index c3a98e47c8..8006ba2195 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/BootstrapSelector.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubsetSelector; using Microsoft.ML.EntryPoints; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubsetSelector; using Microsoft.ML.Transforms; [assembly: LoadableClass(typeof(BootstrapSelector), typeof(BootstrapSelector.Arguments), @@ -16,7 +16,7 @@ [assembly: EntryPointModule(typeof(BootstrapSelector))] -namespace Microsoft.ML.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Trainers.Ensemble.SubsetSelector { internal sealed class BootstrapSelector : BaseSubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs index a142189808..a7f52e6b7b 100644 --- a/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs +++ b/src/Microsoft.ML.Ensemble/Selector/SubsetSelector/RandomPartitionSelector.cs @@ -6,9 +6,9 @@ using System.Collections.Generic; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubsetSelector; using Microsoft.ML.EntryPoints; +using Microsoft.ML.Trainers.Ensemble; +using Microsoft.ML.Trainers.Ensemble.SubsetSelector; using Microsoft.ML.Transforms; [assembly: LoadableClass(typeof(RandomPartitionSelector), typeof(RandomPartitionSelector.Arguments), @@ -16,7 +16,7 @@ [assembly: EntryPointModule(typeof(RandomPartitionSelector))] -namespace Microsoft.ML.Ensemble.Selector.SubsetSelector +namespace Microsoft.ML.Trainers.Ensemble.SubsetSelector { internal sealed class RandomPartitionSelector : BaseSubsetSelector { diff --git a/src/Microsoft.ML.Ensemble/Subset.cs b/src/Microsoft.ML.Ensemble/Subset.cs index 743be33df6..e1e579fd7b 100644 --- a/src/Microsoft.ML.Ensemble/Subset.cs +++ b/src/Microsoft.ML.Ensemble/Subset.cs @@ -5,7 +5,7 @@ using System.Collections; using Microsoft.ML.Data; -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { internal sealed class Subset { diff --git a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs index d63a183f2c..1e734c875c 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Binary/EnsembleTrainer.cs @@ -7,11 +7,8 @@ using System.Linq; using Microsoft.ML; using Microsoft.ML.CommandLine; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; -using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Trainers; +using Microsoft.ML.Trainers.Ensemble; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Training; @@ -22,7 +19,7 @@ [assembly: LoadableClass(typeof(EnsembleTrainer), typeof(EnsembleTrainer.Arguments), typeof(SignatureModelCombiner), "Binary Classification Ensemble Model Combiner", EnsembleTrainer.LoadNameValue, "pe", "ParallelEnsemble")] -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { using TDistPredictor = IDistPredictorProducing; using TScalarPredictor = IPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs index e63f2059e5..d425db8e4f 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleDistributionModelParameters.cs @@ -9,16 +9,15 @@ using Microsoft.Data.DataView; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; +using Microsoft.ML.Trainers.Ensemble; // These are for deserialization from a model repository. [assembly: LoadableClass(typeof(EnsembleDistributionModelParameters), null, typeof(SignatureLoadModel), EnsembleDistributionModelParameters.UserName, EnsembleDistributionModelParameters.LoaderSignature)] -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { using TDistPredictor = IDistPredictorProducing; diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs index 032ff39695..9eb56d5bfd 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParameters.cs @@ -7,17 +7,16 @@ using Microsoft.Data.DataView; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.EntryPoints; using Microsoft.ML.Model; +using Microsoft.ML.Trainers.Ensemble; [assembly: LoadableClass(typeof(EnsembleModelParameters), null, typeof(SignatureLoadModel), EnsembleModelParameters.UserName, EnsembleModelParameters.LoaderSignature)] [assembly: EntryPointModule(typeof(EnsembleModelParameters))] -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { /// /// A class for artifacts of ensembled models. diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs index 5e79bbe41e..f8568cc2d7 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleModelParametersBase.cs @@ -6,12 +6,12 @@ using System.Collections.Generic; using System.IO; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; +using Microsoft.ML.Trainers.Ensemble; -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { public abstract class EnsembleModelParametersBase : ModelParametersBase, IPredictorProducing, ICanSaveInTextFormat, ICanSaveSummary diff --git a/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs b/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs index ef7ebc6d4d..b9aad6228f 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/EnsembleTrainerBase.cs @@ -8,15 +8,13 @@ using System.Threading.Tasks; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble.OutputCombiners; -using Microsoft.ML.Ensemble.Selector; -using Microsoft.ML.Ensemble.Selector.SubsetSelector; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Internallearn; using Microsoft.ML.Internal.Utilities; +using Microsoft.ML.Trainers.Ensemble.SubsetSelector; using Microsoft.ML.Training; -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { using Stopwatch = System.Diagnostics.Stopwatch; diff --git a/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs b/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs index 85f55d8111..48af1cfcfa 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/IModelCombiner.cs @@ -4,7 +4,7 @@ using System.Collections.Generic; -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { public delegate void SignatureModelCombiner(PredictionKind kind); diff --git a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs index 134e58d51d..163b256f1e 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/EnsembleMultiClassModelParameters.cs @@ -7,17 +7,14 @@ using Microsoft.Data.DataView; using Microsoft.ML; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.Model; +using Microsoft.ML.Trainers.Ensemble; [assembly: LoadableClass(typeof(EnsembleMultiClassModelParameters), null, typeof(SignatureLoadModel), EnsembleMultiClassModelParameters.UserName, EnsembleMultiClassModelParameters.LoaderSignature)] -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { - using TVectorPredictor = IPredictorProducing>; - public sealed class EnsembleMultiClassModelParameters : EnsembleModelParametersBase>, IValueMapper { internal const string UserName = "Ensemble Multiclass Executor"; diff --git a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs index 9f5446d327..4420b15ba9 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Multiclass/MulticlassDataPartitionEnsembleTrainer.cs @@ -8,11 +8,8 @@ using Microsoft.ML; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; -using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Trainers; +using Microsoft.ML.Trainers.Ensemble; using Microsoft.ML.Training; [assembly: LoadableClass(MulticlassDataPartitionEnsembleTrainer.Summary, typeof(MulticlassDataPartitionEnsembleTrainer), @@ -24,7 +21,7 @@ [assembly: LoadableClass(typeof(MulticlassDataPartitionEnsembleTrainer), typeof(MulticlassDataPartitionEnsembleTrainer.Arguments), typeof(SignatureModelCombiner), "Multiclass Classification Ensemble Model Combiner", MulticlassDataPartitionEnsembleTrainer.LoadNameValue)] -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { using TVectorPredictor = IPredictorProducing>; /// diff --git a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs index a4075c9c94..e3b7976d51 100644 --- a/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs +++ b/src/Microsoft.ML.Ensemble/Trainer/Regression/RegressionEnsembleTrainer.cs @@ -7,11 +7,8 @@ using System.Linq; using Microsoft.ML; using Microsoft.ML.CommandLine; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; -using Microsoft.ML.Ensemble.Selector; using Microsoft.ML.Internal.Internallearn; -using Microsoft.ML.Trainers; +using Microsoft.ML.Trainers.Ensemble; using Microsoft.ML.Trainers.Online; using Microsoft.ML.Training; @@ -23,7 +20,7 @@ [assembly: LoadableClass(typeof(RegressionEnsembleTrainer), typeof(RegressionEnsembleTrainer.Arguments), typeof(SignatureModelCombiner), "Regression Ensemble Model Combiner", RegressionEnsembleTrainer.LoadNameValue)] -namespace Microsoft.ML.Ensemble +namespace Microsoft.ML.Trainers.Ensemble { using TScalarPredictor = IPredictorProducing; internal sealed class RegressionEnsembleTrainer : EnsembleTrainerBase /// This class implements basic Singular Spectrum Analysis (SSA) model for modeling univariate time-series. diff --git a/src/Microsoft.ML.TimeSeries/EigenUtils.cs b/src/Microsoft.ML.TimeSeries/EigenUtils.cs index 98be26f316..fc8224b94e 100644 --- a/src/Microsoft.ML.TimeSeries/EigenUtils.cs +++ b/src/Microsoft.ML.TimeSeries/EigenUtils.cs @@ -8,7 +8,7 @@ using Microsoft.ML.Internal.Utilities; using Float = System.Single; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { //REVIEW: improve perf with SSE and Multithreading internal static class EigenUtils diff --git a/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs b/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs index dae1fae4f5..29653b2620 100644 --- a/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs +++ b/src/Microsoft.ML.TimeSeries/ExponentialAverageTransform.cs @@ -10,14 +10,14 @@ using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(ExponentialAverageTransform.Summary, typeof(ExponentialAverageTransform), typeof(ExponentialAverageTransform.Arguments), typeof(SignatureDataTransform), ExponentialAverageTransform.UserName, ExponentialAverageTransform.LoaderSignature, ExponentialAverageTransform.ShortName)] [assembly: LoadableClass(ExponentialAverageTransform.Summary, typeof(ExponentialAverageTransform), null, typeof(SignatureLoadDataTransform), ExponentialAverageTransform.UserName, ExponentialAverageTransform.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// ExponentialAverageTransform is a weighted average of the values: ExpAvg(y_t) = a * y_t + (1-a) * ExpAvg(y_(t-1)). diff --git a/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs b/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs index 4090a26ebb..e013f7c671 100644 --- a/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs +++ b/src/Microsoft.ML.TimeSeries/ExtensionsCatalog.cs @@ -3,7 +3,7 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; namespace Microsoft.ML { diff --git a/src/Microsoft.ML.TimeSeries/FftUtils.cs b/src/Microsoft.ML.TimeSeries/FftUtils.cs index a02575c031..28a19a89ed 100644 --- a/src/Microsoft.ML.TimeSeries/FftUtils.cs +++ b/src/Microsoft.ML.TimeSeries/FftUtils.cs @@ -6,7 +6,7 @@ using System.Runtime.InteropServices; using System.Security; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// The utility functions that wrap the native Discrete Fast Fourier Transform functionality from Intel MKL. diff --git a/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs b/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs index 4773fac099..25cf99347b 100644 --- a/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs +++ b/src/Microsoft.ML.TimeSeries/IidAnomalyDetectionBase.cs @@ -9,9 +9,8 @@ using Microsoft.ML.Data; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeries; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// The is the wrapper to that computes the p-values and martingale scores for a supposedly i.i.d input sequence of floats. In other words, it assumes diff --git a/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs b/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs index 3984d6973d..9f5fc85a2d 100644 --- a/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs +++ b/src/Microsoft.ML.TimeSeries/IidChangePointDetector.cs @@ -12,8 +12,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeries; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(IidChangePointDetector.Summary, typeof(IDataTransform), typeof(IidChangePointDetector), typeof(IidChangePointDetector.Options), typeof(SignatureDataTransform), IidChangePointDetector.UserName, IidChangePointDetector.LoaderSignature, IidChangePointDetector.ShortName)] @@ -27,7 +26,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(IidChangePointDetector), null, typeof(SignatureLoadRowMapper), IidChangePointDetector.UserName, IidChangePointDetector.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// This class implements the change point detector transform for an i.i.d. sequence based on adaptive kernel density estimation and martingales. diff --git a/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs b/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs index c6d06e66ae..813043606a 100644 --- a/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs +++ b/src/Microsoft.ML.TimeSeries/IidSpikeDetector.cs @@ -11,8 +11,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeries; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(IidSpikeDetector.Summary, typeof(IDataTransform), typeof(IidSpikeDetector), typeof(IidSpikeDetector.Options), typeof(SignatureDataTransform), IidSpikeDetector.UserName, IidSpikeDetector.LoaderSignature, IidSpikeDetector.ShortName)] @@ -26,7 +25,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(IidSpikeDetector), null, typeof(SignatureLoadRowMapper), IidSpikeDetector.UserName, IidSpikeDetector.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// This class implements the spike detector transform for an i.i.d. sequence based on adaptive kernel density estimation. diff --git a/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs b/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs index 2c51fa13f5..1e04173d49 100644 --- a/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs +++ b/src/Microsoft.ML.TimeSeries/MovingAverageTransform.cs @@ -10,14 +10,14 @@ using Microsoft.ML.Data; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(MovingAverageTransform.Summary, typeof(MovingAverageTransform), typeof(MovingAverageTransform.Arguments), typeof(SignatureDataTransform), "Moving Average Transform", MovingAverageTransform.LoaderSignature, "MoAv")] [assembly: LoadableClass(MovingAverageTransform.Summary, typeof(MovingAverageTransform), null, typeof(SignatureLoadDataTransform), "Moving Average Transform", MovingAverageTransform.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// MovingAverageTransform is a weighted average of the values in diff --git a/src/Microsoft.ML.TimeSeries/PValueTransform.cs b/src/Microsoft.ML.TimeSeries/PValueTransform.cs index a1723ef162..528f8b7fd0 100644 --- a/src/Microsoft.ML.TimeSeries/PValueTransform.cs +++ b/src/Microsoft.ML.TimeSeries/PValueTransform.cs @@ -10,14 +10,14 @@ using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(PValueTransform.Summary, typeof(PValueTransform), typeof(PValueTransform.Arguments), typeof(SignatureDataTransform), PValueTransform.UserName, PValueTransform.LoaderSignature, PValueTransform.ShortName)] [assembly: LoadableClass(PValueTransform.Summary, typeof(PValueTransform), null, typeof(SignatureLoadDataTransform), PValueTransform.UserName, PValueTransform.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// PValueTransform is a sequential transform that computes the empirical p-value of the current value in the series based on the other values in diff --git a/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs b/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs index bfac8ad93a..a4e8c792d0 100644 --- a/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs +++ b/src/Microsoft.ML.TimeSeries/PercentileThresholdTransform.cs @@ -10,14 +10,14 @@ using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(PercentileThresholdTransform.Summary, typeof(PercentileThresholdTransform), typeof(PercentileThresholdTransform.Arguments), typeof(SignatureDataTransform), PercentileThresholdTransform.UserName, PercentileThresholdTransform.LoaderSignature, PercentileThresholdTransform.ShortName)] [assembly: LoadableClass(PercentileThresholdTransform.Summary, typeof(PercentileThresholdTransform), null, typeof(SignatureLoadDataTransform), PercentileThresholdTransform.UserName, PercentileThresholdTransform.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// PercentileThresholdTransform is a sequential transform that decides whether the current value of the time-series belongs to the 'percentile' % of the top values in diff --git a/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs b/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs index 19b1d7f97d..7ba7dd0d25 100644 --- a/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs +++ b/src/Microsoft.ML.TimeSeries/PolynomialUtils.cs @@ -8,7 +8,7 @@ using System.Numerics; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { internal static class PolynomialUtils { diff --git a/src/Microsoft.ML.TimeSeries/PredictionFunction.cs b/src/Microsoft.ML.TimeSeries/PredictionFunction.cs index 0e97713247..5aab239fef 100644 --- a/src/Microsoft.ML.TimeSeries/PredictionFunction.cs +++ b/src/Microsoft.ML.TimeSeries/PredictionFunction.cs @@ -10,7 +10,7 @@ using Microsoft.ML.Core.Data; using Microsoft.ML.Data; -namespace Microsoft.ML.TimeSeries +namespace Microsoft.ML.Transforms.TimeSeries { internal interface IStatefulRowToRowMapper : IRowToRowMapper { diff --git a/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs b/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs index d643435704..b6da0925cc 100644 --- a/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequenceModelerBase.cs @@ -6,7 +6,7 @@ using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// The base container class for the forecast result on a sequence of type . diff --git a/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs b/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs index d9c3750cd6..4bd1cbc87d 100644 --- a/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequentialAnomalyDetectionTransformBase.cs @@ -12,9 +12,9 @@ using Microsoft.ML.Internal.CpuMath; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeries; +using Microsoft.ML.Transforms.TimeSeries; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// The type of the martingale. diff --git a/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs b/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs index d476ba6c64..728d3bc710 100644 --- a/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequentialTransformBase.cs @@ -11,7 +11,7 @@ using Microsoft.ML.Model; using Microsoft.ML.Transforms; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// The box class that is used to box the TInput and TOutput for the LambdaTransform. diff --git a/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs b/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs index e0878e58e1..1c795b1bee 100644 --- a/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs +++ b/src/Microsoft.ML.TimeSeries/SequentialTransformerBase.cs @@ -13,10 +13,8 @@ using Microsoft.ML.Model; using Microsoft.ML.Model.Onnx; using Microsoft.ML.Model.Pfa; -using Microsoft.ML.TimeSeries; -using Microsoft.ML.Transforms; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// diff --git a/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs b/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs index 3f57b81113..103d63f0fa 100644 --- a/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs +++ b/src/Microsoft.ML.TimeSeries/SlidingWindowTransform.cs @@ -7,14 +7,14 @@ using Microsoft.ML; using Microsoft.ML.Data; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(SlidingWindowTransform.Summary, typeof(SlidingWindowTransform), typeof(SlidingWindowTransform.Arguments), typeof(SignatureDataTransform), SlidingWindowTransform.UserName, SlidingWindowTransform.LoaderSignature, SlidingWindowTransform.ShortName)] [assembly: LoadableClass(SlidingWindowTransform.Summary, typeof(SlidingWindowTransform), null, typeof(SignatureLoadDataTransform), SlidingWindowTransform.UserName, SlidingWindowTransform.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// Outputs a sliding window on a time series of type Single. diff --git a/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs b/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs index 84abfacc94..677ddc2488 100644 --- a/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs +++ b/src/Microsoft.ML.TimeSeries/SlidingWindowTransformBase.cs @@ -6,13 +6,11 @@ using Microsoft.Data.DataView; using Microsoft.ML.CommandLine; using Microsoft.ML.Data; -using Microsoft.ML.Data.Conversion; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.Transforms; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// SlidingWindowTransformBase outputs a sliding window as a VBuffer from a series of any type. @@ -104,7 +102,7 @@ private TInput GetNaValue() int index; sch.TryGetColumnIndex(InputColumnName, out index); ColumnType col = sch[index].Type; - TInput nanValue = Conversions.Instance.GetNAOrDefault(col); + TInput nanValue = Data.Conversion.Conversions.Instance.GetNAOrDefault(col); // We store the nan_value here to avoid getting it each time a state is instanciated. return nanValue; diff --git a/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs b/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs index 4cb858485a..3a7411693f 100644 --- a/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs +++ b/src/Microsoft.ML.TimeSeries/SsaAnomalyDetectionBase.cs @@ -10,9 +10,9 @@ using Microsoft.ML.Data; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeries; +using Microsoft.ML.Transforms.TimeSeries; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { public enum ErrorFunction : byte { diff --git a/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs b/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs index 6da61935dc..e6ea241e26 100644 --- a/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs +++ b/src/Microsoft.ML.TimeSeries/SsaChangePointDetector.cs @@ -12,8 +12,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeries; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(SsaChangePointDetector.Summary, typeof(IDataTransform), typeof(SsaChangePointDetector), typeof(SsaChangePointDetector.Options), typeof(SignatureDataTransform), SsaChangePointDetector.UserName, SsaChangePointDetector.LoaderSignature, SsaChangePointDetector.ShortName)] @@ -27,7 +26,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(SsaChangePointDetector), null, typeof(SignatureLoadRowMapper), SsaChangePointDetector.UserName, SsaChangePointDetector.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// This class implements the change point detector transform based on Singular Spectrum modeling of the time-series. diff --git a/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs b/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs index 9a2ad25aab..399bc6b6e0 100644 --- a/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs +++ b/src/Microsoft.ML.TimeSeries/SsaSpikeDetector.cs @@ -11,8 +11,7 @@ using Microsoft.ML.Data; using Microsoft.ML.EntryPoints; using Microsoft.ML.Model; -using Microsoft.ML.TimeSeries; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: LoadableClass(SsaSpikeDetector.Summary, typeof(IDataTransform), typeof(SsaSpikeDetector), typeof(SsaSpikeDetector.Options), typeof(SignatureDataTransform), SsaSpikeDetector.UserName, SsaSpikeDetector.LoaderSignature, SsaSpikeDetector.ShortName)] @@ -26,7 +25,7 @@ [assembly: LoadableClass(typeof(IRowMapper), typeof(SsaSpikeDetector), null, typeof(SignatureLoadRowMapper), SsaSpikeDetector.UserName, SsaSpikeDetector.LoaderSignature)] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// This class implements the spike detector transform based on Singular Spectrum modeling of the time-series. diff --git a/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs b/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs index da5c7b9153..e128a4730c 100644 --- a/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs +++ b/src/Microsoft.ML.TimeSeries/TimeSeriesProcessing.cs @@ -3,11 +3,11 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.EntryPoints; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; [assembly: EntryPointModule(typeof(TimeSeriesProcessingEntryPoints))] -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// Entry points for text anylytics transforms. @@ -26,7 +26,9 @@ internal static CommonOutputs.TransformOutput ExponentialAverage(IHostEnvironmen }; } - [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.IidChangePointDetector.Summary, UserName = TimeSeriesProcessing.IidChangePointDetector.UserName, ShortName = TimeSeriesProcessing.IidChangePointDetector.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeries.IidChangePointDetector.Summary, + UserName = TimeSeries.IidChangePointDetector.UserName, + ShortName = TimeSeries.IidChangePointDetector.ShortName)] internal static CommonOutputs.TransformOutput IidChangePointDetector(IHostEnvironment env, IidChangePointDetector.Options options) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "IidChangePointDetector", options); @@ -38,7 +40,9 @@ internal static CommonOutputs.TransformOutput IidChangePointDetector(IHostEnviro }; } - [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.IidSpikeDetector.Summary, UserName = TimeSeriesProcessing.IidSpikeDetector.UserName, ShortName = TimeSeriesProcessing.IidSpikeDetector.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeries.IidSpikeDetector.Summary, + UserName = TimeSeries.IidSpikeDetector.UserName, + ShortName = TimeSeries.IidSpikeDetector.ShortName)] internal static CommonOutputs.TransformOutput IidSpikeDetector(IHostEnvironment env, IidSpikeDetector.Options options) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "IidSpikeDetector", options); @@ -50,7 +54,9 @@ internal static CommonOutputs.TransformOutput IidSpikeDetector(IHostEnvironment }; } - [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.PercentileThresholdTransform.Summary, UserName = TimeSeriesProcessing.PercentileThresholdTransform.UserName, ShortName = TimeSeriesProcessing.PercentileThresholdTransform.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeries.PercentileThresholdTransform.Summary, + UserName = TimeSeries.PercentileThresholdTransform.UserName, + ShortName = TimeSeries.PercentileThresholdTransform.ShortName)] internal static CommonOutputs.TransformOutput PercentileThresholdTransform(IHostEnvironment env, PercentileThresholdTransform.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "PercentileThresholdTransform", input); @@ -62,7 +68,9 @@ internal static CommonOutputs.TransformOutput PercentileThresholdTransform(IHost }; } - [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.PValueTransform.Summary, UserName = TimeSeriesProcessing.PValueTransform.UserName, ShortName = TimeSeriesProcessing.PValueTransform.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeries.PValueTransform.Summary, + UserName = TimeSeries.PValueTransform.UserName, + ShortName = TimeSeries.PValueTransform.ShortName)] internal static CommonOutputs.TransformOutput PValueTransform(IHostEnvironment env, PValueTransform.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "PValueTransform", input); @@ -74,7 +82,9 @@ internal static CommonOutputs.TransformOutput PValueTransform(IHostEnvironment e }; } - [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.SlidingWindowTransform.Summary, UserName = TimeSeriesProcessing.SlidingWindowTransform.UserName, ShortName = TimeSeriesProcessing.SlidingWindowTransform.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeries.SlidingWindowTransform.Summary, + UserName = TimeSeries.SlidingWindowTransform.UserName, + ShortName = TimeSeries.SlidingWindowTransform.ShortName)] internal static CommonOutputs.TransformOutput SlidingWindowTransform(IHostEnvironment env, SlidingWindowTransform.Arguments input) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "SlidingWindowTransform", input); @@ -86,7 +96,9 @@ internal static CommonOutputs.TransformOutput SlidingWindowTransform(IHostEnviro }; } - [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.SsaChangePointDetector.Summary, UserName = TimeSeriesProcessing.SsaChangePointDetector.UserName, ShortName = TimeSeriesProcessing.SsaChangePointDetector.ShortName)] + [TlcModule.EntryPoint(Desc = TimeSeries.SsaChangePointDetector.Summary, + UserName = TimeSeries.SsaChangePointDetector.UserName, + ShortName = TimeSeries.SsaChangePointDetector.ShortName)] internal static CommonOutputs.TransformOutput SsaChangePointDetector(IHostEnvironment env, SsaChangePointDetector.Options options) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "SsaChangePointDetector", options); @@ -98,8 +110,10 @@ internal static CommonOutputs.TransformOutput SsaChangePointDetector(IHostEnviro }; } - [TlcModule.EntryPoint(Desc = TimeSeriesProcessing.SsaSpikeDetector.Summary, UserName = TimeSeriesProcessing.SsaSpikeDetector.UserName, ShortName = TimeSeriesProcessing.SsaSpikeDetector.ShortName)] - internal static CommonOutputs.TransformOutput SsaSpikeDetector(IHostEnvironment env, SsaSpikeDetector.Options options) + [TlcModule.EntryPoint(Desc = TimeSeries.SsaSpikeDetector.Summary, + UserName = TimeSeries.SsaSpikeDetector.UserName, + ShortName = TimeSeries.SsaSpikeDetector.ShortName)] + public static CommonOutputs.TransformOutput SsaSpikeDetector(IHostEnvironment env, SsaSpikeDetector.Options options) { var h = EntryPointUtils.CheckArgsAndCreateHost(env, "SsaSpikeDetector", options); var view = new SsaSpikeEstimator(h, options).Fit(options.Data).Transform(options.Data); diff --git a/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs b/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs index 82334f7976..e8eb79f1ba 100644 --- a/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs +++ b/src/Microsoft.ML.TimeSeries/TimeSeriesUtils.cs @@ -2,7 +2,7 @@ using System.IO; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.TimeSeries +namespace Microsoft.ML.Transforms.TimeSeries { internal static class TimeSeriesUtils { diff --git a/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs b/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs index b8153cd03f..2ea67dae96 100644 --- a/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs +++ b/src/Microsoft.ML.TimeSeries/TrajectoryMatrix.cs @@ -5,7 +5,7 @@ using System; using Microsoft.ML.Internal.Utilities; -namespace Microsoft.ML.TimeSeriesProcessing +namespace Microsoft.ML.Transforms.TimeSeries { /// /// This class encapsulates the trajectory matrix of a time-series used in Singular Spectrum Analysis (SSA). diff --git a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv index d1a8e3c139..0c60d474be 100644 --- a/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv +++ b/test/BaselineOutput/Common/EntryPoints/core_ep-list.tsv @@ -4,19 +4,19 @@ Data.IDataViewArrayConverter Create an array variable of IDataView Microsoft.ML. Data.PredictorModelArrayConverter Create an array variable of PredictorModel Microsoft.ML.EntryPoints.MacroUtils MakeArray Microsoft.ML.EntryPoints.MacroUtils+ArrayIPredictorModelInput Microsoft.ML.EntryPoints.MacroUtils+ArrayIPredictorModelOutput Data.TextLoader Import a dataset from a text file Microsoft.ML.EntryPoints.ImportTextData TextLoader Microsoft.ML.EntryPoints.ImportTextData+LoaderInput Microsoft.ML.EntryPoints.ImportTextData+Output Models.AnomalyDetectionEvaluator Evaluates an anomaly detection scored dataset. Microsoft.ML.Data.Evaluate AnomalyDetection Microsoft.ML.Data.AnomalyDetectionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.AnomalyPipelineEnsemble Combine anomaly detection models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateAnomalyPipelineEnsemble Microsoft.ML.Ensemble.EnsembleCreator+PipelineAnomalyInput Microsoft.ML.EntryPoints.CommonOutputs+AnomalyDetectionOutput +Models.AnomalyPipelineEnsemble Combine anomaly detection models into an ensemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator CreateAnomalyPipelineEnsemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator+PipelineAnomalyInput Microsoft.ML.EntryPoints.CommonOutputs+AnomalyDetectionOutput Models.BinaryClassificationEvaluator Evaluates a binary classification scored dataset. Microsoft.ML.Data.Evaluate Binary Microsoft.ML.Data.BinaryClassifierMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+ClassificationEvaluateOutput -Models.BinaryEnsemble Combine binary classifiers into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateBinaryEnsemble Microsoft.ML.Ensemble.EnsembleCreator+ClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput -Models.BinaryPipelineEnsemble Combine binary classification models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateBinaryPipelineEnsemble Microsoft.ML.Ensemble.EnsembleCreator+PipelineClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Models.BinaryEnsemble Combine binary classifiers into an ensemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator CreateBinaryEnsemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator+ClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Models.BinaryPipelineEnsemble Combine binary classification models into an ensemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator CreateBinaryPipelineEnsemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator+PipelineClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput Models.ClassificationEvaluator Evaluates a multi class classification scored dataset. Microsoft.ML.Data.Evaluate MultiClass Microsoft.ML.Data.MultiClassMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+ClassificationEvaluateOutput Models.ClusterEvaluator Evaluates a clustering scored dataset. Microsoft.ML.Data.Evaluate Clustering Microsoft.ML.Data.ClusteringMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput Models.CrossValidationResultsCombiner Combine the metric data views returned from cross validation. Microsoft.ML.EntryPoints.CrossValidationMacro CombineMetrics Microsoft.ML.EntryPoints.CrossValidationMacro+CombineMetricsInput Microsoft.ML.EntryPoints.CrossValidationMacro+CombinedOutput Models.CrossValidator Cross validation for general learning Microsoft.ML.EntryPoints.CrossValidationMacro CrossValidate Microsoft.ML.EntryPoints.CrossValidationMacro+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.CrossValidationMacro+Output] Models.CrossValidatorDatasetSplitter Split the dataset into the specified number of cross-validation folds (train and test sets) Microsoft.ML.EntryPoints.CVSplit Split Microsoft.ML.EntryPoints.CVSplit+Input Microsoft.ML.EntryPoints.CVSplit+Output Models.DatasetTransformer Applies a TransformModel to a dataset. Microsoft.ML.EntryPoints.ModelOperations Apply Microsoft.ML.EntryPoints.ModelOperations+ApplyTransformModelInput Microsoft.ML.EntryPoints.ModelOperations+ApplyTransformModelOutput -Models.EnsembleSummary Summarize a pipeline ensemble predictor. Microsoft.ML.Ensemble.PipelineEnsemble Summarize Microsoft.ML.EntryPoints.SummarizePredictor+Input Microsoft.ML.Ensemble.PipelineEnsemble+SummaryOutput +Models.EnsembleSummary Summarize a pipeline ensemble predictor. Microsoft.ML.Trainers.Ensemble.PipelineEnsemble Summarize Microsoft.ML.EntryPoints.SummarizePredictor+Input Microsoft.ML.Trainers.Ensemble.PipelineEnsemble+SummaryOutput Models.FixedPlattCalibrator Apply a Platt calibrator with a fixed slope and offset to an input model Microsoft.ML.Internal.Calibration.Calibrate FixedPlatt Microsoft.ML.Internal.Calibration.Calibrate+FixedPlattInput Microsoft.ML.EntryPoints.CommonOutputs+CalibratorOutput -Models.MultiClassPipelineEnsemble Combine multiclass classifiers into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateMultiClassPipelineEnsemble Microsoft.ML.Ensemble.EnsembleCreator+PipelineClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Models.MultiClassPipelineEnsemble Combine multiclass classifiers into an ensemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator CreateMultiClassPipelineEnsemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator+PipelineClassifierInput Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput Models.MultiOutputRegressionEvaluator Evaluates a multi output regression scored dataset. Microsoft.ML.Data.Evaluate MultiOutputRegression Microsoft.ML.Data.MultiOutputRegressionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput Models.NaiveCalibrator Apply a Naive calibrator to an input model Microsoft.ML.Internal.Calibration.Calibrate Naive Microsoft.ML.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.EntryPoints.CommonOutputs+CalibratorOutput Models.OneVersusAll One-vs-All macro (OVA) Microsoft.ML.EntryPoints.OneVersusAllMacro OneVersusAll Microsoft.ML.EntryPoints.OneVersusAllMacro+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.OneVersusAllMacro+Output] @@ -26,23 +26,23 @@ Models.PAVCalibrator Apply a PAV calibrator to an input model Microsoft.ML.Inter Models.PlattCalibrator Apply a Platt calibrator to an input model Microsoft.ML.Internal.Calibration.Calibrate Platt Microsoft.ML.Internal.Calibration.Calibrate+NoArgumentsInput Microsoft.ML.EntryPoints.CommonOutputs+CalibratorOutput Models.QuantileRegressionEvaluator Evaluates a quantile regression scored dataset. Microsoft.ML.Data.Evaluate QuantileRegression Microsoft.ML.Data.QuantileRegressionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput Models.RankerEvaluator Evaluates a ranking scored dataset. Microsoft.ML.Data.Evaluate Ranking Microsoft.ML.Data.RankerMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.RegressionEnsemble Combine regression models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateRegressionEnsemble Microsoft.ML.Ensemble.EnsembleCreator+RegressionInput Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Models.RegressionEnsemble Combine regression models into an ensemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator CreateRegressionEnsemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator+RegressionInput Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Models.RegressionEvaluator Evaluates a regression scored dataset. Microsoft.ML.Data.Evaluate Regression Microsoft.ML.Data.RegressionMamlEvaluator+Arguments Microsoft.ML.EntryPoints.CommonOutputs+CommonEvaluateOutput -Models.RegressionPipelineEnsemble Combine regression models into an ensemble Microsoft.ML.Ensemble.EnsembleCreator CreateRegressionPipelineEnsemble Microsoft.ML.Ensemble.EnsembleCreator+PipelineRegressionInput Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Models.RegressionPipelineEnsemble Combine regression models into an ensemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator CreateRegressionPipelineEnsemble Microsoft.ML.Trainers.Ensemble.EnsembleCreator+PipelineRegressionInput Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Models.Summarizer Summarize a linear regression predictor. Microsoft.ML.EntryPoints.SummarizePredictor Summarize Microsoft.ML.EntryPoints.SummarizePredictor+Input Microsoft.ML.EntryPoints.CommonOutputs+SummaryOutput Models.TrainTestEvaluator General train test for any supported evaluator Microsoft.ML.EntryPoints.TrainTestMacro TrainTest Microsoft.ML.EntryPoints.TrainTestMacro+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MacroOutput`1[Microsoft.ML.EntryPoints.TrainTestMacro+Output] -TimeSeriesProcessingEntryPoints.ExponentialAverage Applies a Exponential average on a time series. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints ExponentialAverage Microsoft.ML.TimeSeriesProcessing.ExponentialAverageTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessingEntryPoints.IidChangePointDetector This transform detects the change-points in an i.i.d. sequence using adaptive kernel density estimation and martingales. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints IidChangePointDetector Microsoft.ML.TimeSeriesProcessing.IidChangePointDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessingEntryPoints.IidSpikeDetector This transform detects the spikes in a i.i.d. sequence using adaptive kernel density estimation. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints IidSpikeDetector Microsoft.ML.TimeSeriesProcessing.IidSpikeDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessingEntryPoints.PercentileThresholdTransform Detects the values of time-series that are in the top percentile of the sliding window. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints PercentileThresholdTransform Microsoft.ML.TimeSeriesProcessing.PercentileThresholdTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessingEntryPoints.PValueTransform This P-Value transform calculates the p-value of the current input in the sequence with regard to the values in the sliding window. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints PValueTransform Microsoft.ML.TimeSeriesProcessing.PValueTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessingEntryPoints.SlidingWindowTransform Returns the last values for a time series [y(t-d-l+1), y(t-d-l+2), ..., y(t-l-1), y(t-l)] where d is the size of the window, l the lag and y is a Float. Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints SlidingWindowTransform Microsoft.ML.TimeSeriesProcessing.SlidingWindowTransformBase`1+Arguments[System.Single] Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessingEntryPoints.SsaChangePointDetector This transform detects the change-points in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints SsaChangePointDetector Microsoft.ML.TimeSeriesProcessing.SsaChangePointDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput -TimeSeriesProcessingEntryPoints.SsaSpikeDetector This transform detects the spikes in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.TimeSeriesProcessing.TimeSeriesProcessingEntryPoints SsaSpikeDetector Microsoft.ML.TimeSeriesProcessing.SsaSpikeDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.ExponentialAverage Applies a Exponential average on a time series. Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints ExponentialAverage Microsoft.ML.Transforms.TimeSeries.ExponentialAverageTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.IidChangePointDetector This transform detects the change-points in an i.i.d. sequence using adaptive kernel density estimation and martingales. Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints IidChangePointDetector Microsoft.ML.Transforms.TimeSeries.IidChangePointDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.IidSpikeDetector This transform detects the spikes in a i.i.d. sequence using adaptive kernel density estimation. Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints IidSpikeDetector Microsoft.ML.Transforms.TimeSeries.IidSpikeDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.PercentileThresholdTransform Detects the values of time-series that are in the top percentile of the sliding window. Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints PercentileThresholdTransform Microsoft.ML.Transforms.TimeSeries.PercentileThresholdTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.PValueTransform This P-Value transform calculates the p-value of the current input in the sequence with regard to the values in the sliding window. Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints PValueTransform Microsoft.ML.Transforms.TimeSeries.PValueTransform+Arguments Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.SlidingWindowTransform Returns the last values for a time series [y(t-d-l+1), y(t-d-l+2), ..., y(t-l-1), y(t-l)] where d is the size of the window, l the lag and y is a Float. Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints SlidingWindowTransform Microsoft.ML.Transforms.TimeSeries.SlidingWindowTransformBase`1+Arguments[System.Single] Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.SsaChangePointDetector This transform detects the change-points in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints SsaChangePointDetector Microsoft.ML.Transforms.TimeSeries.SsaChangePointDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput +TimeSeriesProcessingEntryPoints.SsaSpikeDetector This transform detects the spikes in a seasonal time-series using Singular Spectrum Analysis (SSA). Microsoft.ML.Transforms.TimeSeries.TimeSeriesProcessingEntryPoints SsaSpikeDetector Microsoft.ML.Transforms.TimeSeries.SsaSpikeDetector+Options Microsoft.ML.EntryPoints.CommonOutputs+TransformOutput Trainers.AveragedPerceptronBinaryClassifier Averaged Perceptron Binary Classifier. Microsoft.ML.Trainers.Online.AveragedPerceptronTrainer TrainBinary Microsoft.ML.Trainers.Online.AveragedPerceptronTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.EnsembleBinaryClassifier Train binary ensemble. Microsoft.ML.Ensemble.Ensemble CreateBinaryEnsemble Microsoft.ML.Ensemble.EnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput -Trainers.EnsembleClassification Train multiclass ensemble. Microsoft.ML.Ensemble.Ensemble CreateMultiClassEnsemble Microsoft.ML.Ensemble.MulticlassDataPartitionEnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput -Trainers.EnsembleRegression Train regression ensemble. Microsoft.ML.Ensemble.Ensemble CreateRegressionEnsemble Microsoft.ML.Ensemble.RegressionEnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput +Trainers.EnsembleBinaryClassifier Train binary ensemble. Microsoft.ML.Trainers.Ensemble.Ensemble CreateBinaryEnsemble Microsoft.ML.Trainers.Ensemble.EnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput +Trainers.EnsembleClassification Train multiclass ensemble. Microsoft.ML.Trainers.Ensemble.Ensemble CreateMultiClassEnsemble Microsoft.ML.Trainers.Ensemble.MulticlassDataPartitionEnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+MulticlassClassificationOutput +Trainers.EnsembleRegression Train regression ensemble. Microsoft.ML.Trainers.Ensemble.Ensemble CreateRegressionEnsemble Microsoft.ML.Trainers.Ensemble.RegressionEnsembleTrainer+Arguments Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Trainers.FastForestBinaryClassifier Uses a random forest learner to perform binary classification. Microsoft.ML.Trainers.FastTree.FastForest TrainBinary Microsoft.ML.Trainers.FastTree.FastForestClassification+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput Trainers.FastForestRegressor Trains a random forest to fit target values using least-squares. Microsoft.ML.Trainers.FastTree.FastForest TrainRegression Microsoft.ML.Trainers.FastTree.FastForestRegression+Options Microsoft.ML.EntryPoints.CommonOutputs+RegressionOutput Trainers.FastTreeBinaryClassifier Uses a logit-boost boosted tree learner to perform binary classification. Microsoft.ML.Trainers.FastTree.FastTree TrainBinary Microsoft.ML.Trainers.FastTree.FastTreeBinaryClassificationTrainer+Options Microsoft.ML.EntryPoints.CommonOutputs+BinaryClassificationOutput diff --git a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs index 4f5686c3d7..8b0c46b817 100644 --- a/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs +++ b/test/Microsoft.ML.Core.Tests/UnitTests/TestEntryPoints.cs @@ -12,8 +12,6 @@ using Microsoft.ML.Core.Tests.UnitTests; using Microsoft.ML.Data; using Microsoft.ML.Data.IO; -using Microsoft.ML.Ensemble; -using Microsoft.ML.Ensemble.OutputCombiners; using Microsoft.ML.EntryPoints; using Microsoft.ML.EntryPoints.JsonUtils; using Microsoft.ML.ImageAnalytics; @@ -23,8 +21,8 @@ using Microsoft.ML.LightGBM; using Microsoft.ML.Model.Onnx; using Microsoft.ML.TestFramework.Attributes; -using Microsoft.ML.TimeSeriesProcessing; using Microsoft.ML.Trainers; +using Microsoft.ML.Trainers.Ensemble; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.HalLearners; using Microsoft.ML.Trainers.PCA; @@ -34,6 +32,7 @@ using Microsoft.ML.Transforms.Normalizers; using Microsoft.ML.Transforms.Projections; using Microsoft.ML.Transforms.Text; +using Microsoft.ML.Transforms.TimeSeries; using Newtonsoft.Json; using Newtonsoft.Json.Linq; using Xunit; diff --git a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs index 0af5ad72b5..464fd0dc59 100644 --- a/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs +++ b/test/Microsoft.ML.Predictor.Tests/TestPredictors.cs @@ -15,12 +15,12 @@ namespace Microsoft.ML.RunTests using Microsoft.Data.DataView; using Microsoft.ML; using Microsoft.ML.Data; - using Microsoft.ML.Ensemble; using Microsoft.ML.EntryPoints; using Microsoft.ML.Internal.Utilities; using Microsoft.ML.LightGBM; using Microsoft.ML.TestFramework; using Microsoft.ML.Trainers; + using Microsoft.ML.Trainers.Ensemble; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.HalLearners; using Microsoft.ML.Trainers.Online; diff --git a/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs b/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs index 36fccc7980..51f9c7e465 100644 --- a/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs +++ b/test/Microsoft.ML.TestFramework/EnvironmentExtensions.cs @@ -3,9 +3,9 @@ // See the LICENSE file in the project root for more information. using Microsoft.ML.Data; -using Microsoft.ML.Ensemble; using Microsoft.ML.EntryPoints; using Microsoft.ML.Trainers; +using Microsoft.ML.Trainers.Ensemble; using Microsoft.ML.Trainers.FastTree; using Microsoft.ML.Trainers.KMeans; using Microsoft.ML.Trainers.PCA; diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs index e79da61465..bfb8a7999c 100644 --- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs +++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeries.cs @@ -5,7 +5,7 @@ using System.IO; using System.Linq; using Microsoft.ML.TestFramework.Attributes; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; using Xunit; using Xunit.Abstractions; diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs index 9b64a68abd..8b190e0769 100644 --- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs +++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesDirectApi.cs @@ -8,8 +8,7 @@ using Microsoft.ML.Data; using Microsoft.ML.RunTests; using Microsoft.ML.TestFramework.Attributes; -using Microsoft.ML.TimeSeries; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; using Xunit; namespace Microsoft.ML.Tests diff --git a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs index e65c9da724..fa77255e3c 100644 --- a/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs +++ b/test/Microsoft.ML.TimeSeries.Tests/TimeSeriesEstimatorTests.cs @@ -5,7 +5,7 @@ using System.Collections.Generic; using Microsoft.ML.Data; using Microsoft.ML.RunTests; -using Microsoft.ML.TimeSeriesProcessing; +using Microsoft.ML.Transforms.TimeSeries; using Xunit; using Xunit.Abstractions;