143 references to TrainerName
Microsoft.ML.AutoML (87)
API\ExperimentBase.cs (2)
29private readonly IEnumerable<TrainerName> _trainerAllowList; 36IEnumerable<TrainerName> trainerAllowList)
Experiment\Experiment.cs (2)
24private readonly IEnumerable<TrainerName> _trainerAllowList; 46IEnumerable<TrainerName> trainerAllowList,
Experiment\RecipeInference.cs (1)
16ColumnInformation columnInfo, IEnumerable<TrainerName> trainerAllowList)
Experiment\SuggestedPipeline.cs (3)
86var trainerName = (TrainerName)Enum.Parse(typeof(TrainerName), pipelineNode.Name);
Experiment\SuggestedTrainer.cs (1)
14public TrainerName TrainerName { get; }
PipelineSuggesters\PipelineSuggester.cs (2)
36IEnumerable<TrainerName> trainerAllowList = null) 113var selectedTrainerNames = new HashSet<TrainerName>(selectedTrainers.Select(t => t.TrainerName));
TrainerExtensions\TrainerExtensionCatalog.cs (38)
13private static readonly IDictionary<TrainerName, Type> _trainerNamesToExtensionTypes = 14new Dictionary<TrainerName, Type>() 16{ TrainerName.AveragedPerceptronBinary, typeof(AveragedPerceptronBinaryExtension) }, 17{ TrainerName.AveragedPerceptronOva, typeof(AveragedPerceptronOvaExtension) }, 18{ TrainerName.FastForestBinary, typeof(FastForestBinaryExtension) }, 19{ TrainerName.FastForestOva, typeof(FastForestOvaExtension) }, 20{ TrainerName.FastForestRegression, typeof(FastForestRegressionExtension) }, 21{ TrainerName.FastTreeBinary, typeof(FastTreeBinaryExtension) }, 22{ TrainerName.FastTreeOva, typeof(FastTreeOvaExtension) }, 23{ TrainerName.FastTreeRegression, typeof(FastTreeRegressionExtension) }, 24{ TrainerName.FastTreeTweedieRegression, typeof(FastTreeTweedieRegressionExtension) }, 25{ TrainerName.LightGbmBinary, typeof(LightGbmBinaryExtension) }, 26{ TrainerName.LightGbmMulti, typeof(LightGbmMultiExtension) }, 27{ TrainerName.LightGbmRegression, typeof(LightGbmRegressionExtension) }, 28{ TrainerName.LinearSvmBinary, typeof(LinearSvmBinaryExtension) }, 29{ TrainerName.LinearSvmOva, typeof(LinearSvmOvaExtension) }, 30{ TrainerName.LbfgsLogisticRegressionBinary, typeof(LbfgsLogisticRegressionBinaryExtension) }, 31{ TrainerName.LbfgsMaximumEntropyMulti, typeof(LbfgsMaximumEntropyMultiExtension) }, 32{ TrainerName.LbfgsLogisticRegressionOva, typeof(LbfgsLogisticRegressionOvaExtension) }, 33{ TrainerName.OnlineGradientDescentRegression, typeof(OnlineGradientDescentRegressionExtension) }, 34{ TrainerName.OlsRegression, typeof(OlsRegressionExtension) }, 35{ TrainerName.LbfgsPoissonRegression, typeof(LbfgsPoissonRegressionExtension) }, 36{ TrainerName.SdcaLogisticRegressionBinary, typeof(SdcaLogisticRegressionBinaryExtension) }, 37{ TrainerName.SdcaMaximumEntropyMulti, typeof(SdcaMaximumEntropyMultiExtension) }, 38{ TrainerName.SdcaRegression, typeof(SdcaRegressionExtension) }, 39{ TrainerName.SgdCalibratedBinary, typeof(SgdCalibratedBinaryExtension) }, 40{ TrainerName.SgdCalibratedOva, typeof(SgdCalibratedOvaExtension) }, 41{ TrainerName.SymbolicSgdLogisticRegressionBinary, typeof(SymbolicSgdLogisticRegressionBinaryExtension) }, 42{ TrainerName.SymbolicSgdLogisticRegressionOva, typeof(SymbolicSgdLogisticRegressionOvaExtension) }, 43{ TrainerName.MatrixFactorization, typeof(MatrixFactorizationExtension) }, 44{ TrainerName.ImageClassification, typeof(ImageClassificationExtension) }, 45{ TrainerName.LightGbmRanking, typeof(LightGbmRankingExtension) }, 46{ TrainerName.FastTreeRanking, typeof(FastTreeRankingExtension) }, 49private static readonly IDictionary<Type, TrainerName> _extensionTypesToTrainerNames = 52public static TrainerName GetTrainerName(ITrainerExtension trainerExtension) 57public static ITrainerExtension GetTrainerExtension(TrainerName trainerName) 64IEnumerable<TrainerName> allowList, ColumnInformation columnInfo) 106allowList = new HashSet<TrainerName>(allowList);
TrainerExtensions\TrainerExtensionUtil.cs (38)
105Name = TrainerName.Ova.ToString(), 117public static PipelineNode BuildPipelineNode(TrainerName trainerName, IEnumerable<SweepableParam> sweepParams, 134public static PipelineNode BuildLightGbmPipelineNode(TrainerName trainerName, IEnumerable<SweepableParam> sweepParams, 193public static ParameterSet BuildParameterSet(TrainerName trainerName, IDictionary<string, object> props) 198if (trainerName == TrainerName.LightGbmBinary || trainerName == TrainerName.LightGbmMulti || 199trainerName == TrainerName.LightGbmRegression || trainerName == TrainerName.LightGbmRanking) 301public static TrainerName GetTrainerName(BinaryClassificationTrainer binaryTrainer) 306return TrainerName.FastForestBinary; 308return TrainerName.FastTreeBinary; 310return TrainerName.LightGbmBinary; 312return TrainerName.LbfgsLogisticRegressionBinary; 314return TrainerName.SdcaLogisticRegressionBinary; 321public static TrainerName GetTrainerName(MulticlassClassificationTrainer multiTrainer) 326return TrainerName.FastForestOva; 328return TrainerName.FastTreeOva; 330return TrainerName.LightGbmMulti; 332return TrainerName.LbfgsMaximumEntropyMulti; 334return TrainerName.LbfgsLogisticRegressionOva; 336return TrainerName.SdcaMaximumEntropyMulti; 343public static TrainerName GetTrainerName(RegressionTrainer regressionTrainer) 348return TrainerName.FastForestRegression; 350return TrainerName.FastTreeRegression; 352return TrainerName.FastTreeTweedieRegression; 354return TrainerName.LightGbmRegression; 356return TrainerName.LbfgsPoissonRegression; 358return TrainerName.SdcaRegression; 365public static TrainerName GetTrainerName(RankingTrainer rankingTrainer) 370return TrainerName.FastTreeRanking; 372return TrainerName.LightGbmRanking; 379public static TrainerName GetTrainerName(RecommendationTrainer recommendationTrainer) 384return TrainerName.MatrixFactorization; 391public static IEnumerable<TrainerName> GetTrainerNames(IEnumerable<BinaryClassificationTrainer> binaryTrainers) 396public static IEnumerable<TrainerName> GetTrainerNames(IEnumerable<MulticlassClassificationTrainer> multiTrainers) 401public static IEnumerable<TrainerName> GetTrainerNames(IEnumerable<RegressionTrainer> regressionTrainers) 406public static IEnumerable<TrainerName> GetTrainerNames(IEnumerable<RecommendationTrainer> recommendationTrainers) 411public static IEnumerable<TrainerName> GetTrainerNames(IEnumerable<RankingTrainer> rankingTrainers)
Microsoft.ML.AutoML.Tests (13)
TrainerExtensionsTests.cs (13)
27var trainerNames = Enum.GetValues(typeof(TrainerName)).Cast<TrainerName>() 28.Except(new[] { TrainerName.Ova }); 29foreach (var trainerName in trainerNames) 34if (trainerName != TrainerName.ImageClassification) 56var extension = TrainerExtensionCatalog.GetTrainerExtension(TrainerName.ImageClassification); 325var binaryParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmBinary, props); 326var multiParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmMulti, props); 327var regressionParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmRegression, props); 328var rankingParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.LightGbmRanking, props); 348var sdcaParams = TrainerExtensionUtil.BuildParameterSet(TrainerName.SdcaLogisticRegressionBinary, props); 411var allowList = new[] { TrainerName.AveragedPerceptronBinary, TrainerName.FastForestBinary };
Microsoft.ML.CodeGenerator (41)
CodeGenerator\CSharp\CodeGenerator.cs (15)
27private static readonly HashSet<string> _recommendationTrainers = new HashSet<string>() { TrainerName.MatrixFactorization.ToString() }; 28private static readonly HashSet<string> _lightGbmTrainers = new HashSet<string>() { TrainerName.LightGbmBinary.ToString(), TrainerName.LightGbmMulti.ToString(), 29TrainerName.LightGbmRegression.ToString(), TrainerName.LightGbmRanking.ToString() }; 30private static readonly HashSet<string> _mklComponentsTrainers = new HashSet<string>() { TrainerName.OlsRegression.ToString(), TrainerName.SymbolicSgdLogisticRegressionBinary.ToString() }; 31private static readonly HashSet<string> _fastTreeTrainers = new HashSet<string>() { TrainerName.FastForestBinary.ToString(), TrainerName.FastForestRegression.ToString(), 32TrainerName.FastTreeBinary.ToString(), TrainerName.FastTreeRegression.ToString(), TrainerName.FastTreeTweedieRegression.ToString(), TrainerName.FastTreeRanking.ToString() }; 34private static readonly HashSet<string> _imageClassificationTrainers = new HashSet<string>() { TrainerName.ImageClassification.ToString() }; 106if (currentNode.Name == TrainerName.Ova.ToString())
CodeGenerator\CSharp\TrainerGeneratorFactory.cs (26)
22if (Enum.TryParse(node.Name, out TrainerName trainer)) 26case TrainerName.LightGbmBinary: 28case TrainerName.LightGbmMulti: 30case TrainerName.LightGbmRegression: 32case TrainerName.AveragedPerceptronBinary: 34case TrainerName.FastForestBinary: 36case TrainerName.FastForestRegression: 38case TrainerName.FastTreeBinary: 40case TrainerName.FastTreeRegression: 42case TrainerName.FastTreeTweedieRegression: 44case TrainerName.LinearSvmBinary: 46case TrainerName.LbfgsLogisticRegressionBinary: 48case TrainerName.LbfgsMaximumEntropyMulti: 50case TrainerName.OnlineGradientDescentRegression: 52case TrainerName.OlsRegression: 54case TrainerName.LbfgsPoissonRegression: 56case TrainerName.SdcaLogisticRegressionBinary: 58case TrainerName.SdcaMaximumEntropyMulti: 60case TrainerName.SdcaRegression: 62case TrainerName.SgdCalibratedBinary: 64case TrainerName.SymbolicSgdLogisticRegressionBinary: 66case TrainerName.Ova: 68case TrainerName.ImageClassification: 70case TrainerName.MatrixFactorization: 72case TrainerName.LightGbmRanking: 74case TrainerName.FastTreeRanking:
Microsoft.ML.CodeGenerator.Tests (2)
ApprovalTests\ConsoleCodeGeneratorTests.cs (2)
560var matrixPipelineNode = new PipelineNode(nameof(TrainerName.MatrixFactorization), PipelineNodeType.Trainer, "Features", "Score", hyperParam); 729var lightGbmPipelineNode = new PipelineNode(nameof(TrainerName.LightGbmRanking), PipelineNodeType.Trainer, "Features", "Score", hyperParam);