FastForest( this SweepableBinaryClassificationTrainers trainer, string labelColumnName = "Label", string featureColumnName = "Features", SweepableOption <FastForestBinaryTrainer.Options> optionBuilder = null, FastForestBinaryTrainer.Options defaultOption = null) { var context = trainer.Context; if (optionBuilder == null) { optionBuilder = FastForestBinaryTrainerSweepableOptions.Default; } optionBuilder.SetDefaultOption(defaultOption); return(context.AutoML().CreateSweepableEstimator( (context, option) => { option.LabelColumnName = labelColumnName; option.FeatureColumnName = featureColumnName; return context.BinaryClassification.Trainers.FastForest(option); }, optionBuilder, new string[] { labelColumnName, featureColumnName }, new string[] { PredictedLabel }, nameof(FastForestBinaryTrainer))); }
OnlineGradientDescent( this SweepableRegressionTrainers trainers, string labelColumnName = "Label", string featureColumnName = "Features", SweepableOption <OnlineGradientDescentTrainer.Options> optionSweeper = null, OnlineGradientDescentTrainer.Options defaultOption = null) { var context = trainers.Context; if (optionSweeper == null) { optionSweeper = OnlineGradientDescentTrainerSweepableOptions.Default; } optionSweeper.SetDefaultOption(defaultOption); return(context.AutoML().CreateSweepableEstimator( (context, option) => { option.LabelColumnName = labelColumnName; option.FeatureColumnName = featureColumnName; return context.Regression.Trainers.OnlineGradientDescent(option); }, optionSweeper, new string[] { labelColumnName, featureColumnName }, new string[] { Score }, nameof(OnlineGradientDescentTrainer))); }
SdcaNonCalibreated(this SweepableMultiClassificationTrainers trainer, string labelColumnName = "Label", string featureColumnName = "Features", SweepableOption <SdcaNonCalibratedMulticlassTrainer.Options> optionBuilder = null, SdcaNonCalibratedMulticlassTrainer.Options defaultOption = null) { var context = trainer.Context; if (optionBuilder == null) { optionBuilder = SdcaNonCalibratedMulticlassTrainerSweepableOptions.Default; } optionBuilder.SetDefaultOption(defaultOption); return(context.AutoML().CreateSweepableEstimator( (context, option) => { option.LabelColumnName = labelColumnName; option.FeatureColumnName = featureColumnName; return context.MulticlassClassification.Trainers.SdcaNonCalibrated(option); }, optionBuilder, trainerName: nameof(SdcaNonCalibratedMulticlassTrainer), inputs: new string[] { featureColumnName }, outputs: new string[] { PredictedLabel })); }
LightGbm(this SweepableMultiClassificationTrainers trainer, string labelColumnName = "Label", string featureColumnName = "Features", SweepableOption <LightGbmMulticlassTrainer.Options> optionBuilder = null, LightGbmMulticlassTrainer.Options defaultOption = null) { var context = trainer.Context; if (optionBuilder == null) { optionBuilder = LightGbmMulticlassTrainerSweepableOptions.Default; } optionBuilder.SetDefaultOption(defaultOption); return(context.AutoML().CreateSweepableEstimator( (context, option) => { if (defaultOption != null) { Util.CopyFieldsTo(defaultOption, option); } option.LabelColumnName = labelColumnName; option.FeatureColumnName = featureColumnName; return context.MulticlassClassification.Trainers.LightGbm(option); }, optionBuilder, trainerName: nameof(LightGbmMulticlassTrainer), inputs: new string[] { featureColumnName }, outputs: new string[] { PredictedLabel })); }
public static SweepableEstimator <TNewTrain, TOption> CreateSweepableEstimator <TNewTrain, TOption>(Func <TOption, TNewTrain> estimatorFactory, SweepableOption <TOption> optionBuilder, TransformerScope scope = TransformerScope.Everything, string estimatorName = null, string[] inputs = null, string[] outputs = null) where TNewTrain : IEstimator <ITransformer> where TOption : class { return(new SweepableEstimator <TNewTrain, TOption>(estimatorFactory, optionBuilder, scope, estimatorName, inputs, outputs)); }