public static CommonOutputs.TransformOutput Featurizer(IHostEnvironment env, TreeEnsembleFeaturizerTransform.ArgumentsForEntryPoint input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("TreeFeaturizerTransform"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = TreeEnsembleFeaturizerTransform.CreateForEntryPoint(env, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.TransformOutput KeyToText(IHostEnvironment env, KeyToValueMappingTransformer.Arguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("KeyToValue"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = KeyToValueMappingTransformer.Create(host, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.RankingOutput TrainRanking(IHostEnvironment env, LightGbmRankingTrainer.Options input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("TrainLightGBM"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); return(TrainerEntryPointsUtils.Train <LightGbmRankingTrainer.Options, CommonOutputs.RankingOutput>(host, input, () => new LightGbmRankingTrainer(host, input), getLabel: () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.LabelColumnName), getWeight: () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.ExampleWeightColumnName), getGroup: () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.RowGroupColumnName))); }
public static CommonOutputs.TransformOutput MutualInformationSelect(IHostEnvironment env, MutualInformationFeatureSelectingEstimator.Options input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("MutualInformationSelect"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = MutualInformationFeatureSelectingEstimator.Create(host, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, XGBoostArguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("Train" + EntryPointName); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); return(LearnerEntryPointsUtils.Train <XGBoostArguments, CommonOutputs.BinaryClassificationOutput>(host, input, () => new XGBoostBinaryTrainer(host, input), getLabel: () => LearnerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.LabelColumn), getWeight: () => LearnerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.WeightColumn))); }
public static CommonOutputs.RegressionOutput TrainRegression(IHostEnvironment env, FastTreeRegressionTrainer.Options input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("TrainFastTree"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); return(TrainerEntryPointsUtils.Train <FastTreeRegressionTrainer.Options, CommonOutputs.RegressionOutput>(host, input, () => new FastTreeRegressionTrainer(host, input), () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.LabelColumnName), () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.ExampleWeightColumnName), () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.RowGroupColumnName))); }
public static CommonOutputs.TransformOutput LabelIndicator(IHostEnvironment env, Options input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("LabelIndictator"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = Create(host, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.TransformOutput TextToKey(IHostEnvironment env, TermTransform.Arguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("Term"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = TermTransform.Create(host, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModel(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.TransformOutput CountSelect(IHostEnvironment env, CountFeatureSelectionTransformer.Arguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("CountSelect"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = CountFeatureSelectionTransformer.Create(host, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModel(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.TransformOutput Nop(IHostEnvironment env, NopInput input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("Nop"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = CreateIfNeeded(host, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModel(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastTreeBinaryClassificationTrainer.Arguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("TrainFastTree"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); return(LearnerEntryPointsUtils.Train <FastTreeBinaryClassificationTrainer.Arguments, CommonOutputs.BinaryClassificationOutput>(host, input, () => new FastTreeBinaryClassificationTrainer(host, input), () => LearnerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.LabelColumn), () => LearnerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.WeightColumn), () => LearnerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.GroupIdColumn))); }
public static CommonOutputs.TransformOutput CatTransformHash(IHostEnvironment env, OneHotHashEncoding.Arguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("CatTransformDict"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = OneHotHashEncoding.Create(host, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.TransformOutput LogMeanVar(IHostEnvironment env, NormalizeTransform.LogMeanVarArguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("LogMeanVar"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); var xf = NormalizeTransform.Create(host, input, input.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModel(env, xf, input.Data), OutputData = xf }); }
public static CommonOutputs.BinaryClassificationOutput TrainBinary(IHostEnvironment env, FastForestBinaryTrainer.Options input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("TrainFastForest"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); return(TrainerEntryPointsUtils.Train <FastForestBinaryTrainer.Options, CommonOutputs.BinaryClassificationOutput>(host, input, () => new FastForestBinaryTrainer(host, input), () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.LabelColumnName), () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.ExampleWeightColumnName), () => TrainerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.RowGroupColumnName), calibrator: input.Calibrator, maxCalibrationExamples: input.MaxCalibrationExamples)); }
public static PermutationFeatureImportanceOutput PermutationFeatureImportance(IHostEnvironment env, PermutationFeatureImportanceArguments input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("Pfi"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); input.PredictorModel.PrepareData(env, input.Data, out RoleMappedData roleMappedData, out IPredictor predictor); Contracts.Assert(predictor != null, "No predictor found in model"); IDataView result = PermutationFeatureImportanceUtils.GetMetrics(env, predictor, roleMappedData, input); return(new PermutationFeatureImportanceOutput { Metrics = result }); }
public static CommonOutputs.TransformOutput ConcatColumns(IHostEnvironment env, ColumnCopyingTransformer.Options input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("PrefixConcatColumns"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); // Get all column names with preserving order. var colNames = new List <string>(input.Data.Schema.Count); for (int i = 0; i < input.Data.Schema.Count; i++) { colNames.Add(input.Data.Schema[i].Name); } // Iterate through input options, find matching source columns, create new input options var inputOptions = new ColumnConcatenatingTransformer.Options() { Data = input.Data }; var columns = new List <ColumnConcatenatingTransformer.Column>(input.Columns.Length); foreach (var col in input.Columns) { var newCol = new ColumnConcatenatingTransformer.Column(); newCol.Name = col.Name; var prefix = col.Source; newCol.Source = colNames.Where(x => x.StartsWith(prefix, StringComparison.InvariantCulture)).ToArray(); if (newCol.Source.Length == 0) { throw new ArgumentOutOfRangeException("No matching columns found for prefix: " + prefix); } columns.Add(newCol); } inputOptions.Columns = columns.ToArray(); var xf = ColumnConcatenatingTransformer.Create(env, inputOptions, inputOptions.Data); return(new CommonOutputs.TransformOutput { Model = new TransformModelImpl(env, xf, inputOptions.Data), OutputData = xf }); }
public static SummaryOutput Summarize(IHostEnvironment env, SummarizePredictor.Input input) { Contracts.CheckValue(env, nameof(env)); var host = env.Register("PipelineEnsemblePredictor"); host.CheckValue(input, nameof(input)); EntryPointUtils.CheckInputArgs(host, input); input.PredictorModel.PrepareData(host, new EmptyDataView(host, input.PredictorModel.TransformModel.InputSchema), out RoleMappedData rmd, out IPredictor predictor ); var calibrated = predictor as CalibratedPredictorBase; while (calibrated != null) { predictor = calibrated.SubPredictor; calibrated = predictor as CalibratedPredictorBase; } var ensemble = predictor as SchemaBindablePipelineEnsembleBase; host.CheckUserArg(ensemble != null, nameof(input.PredictorModel.Predictor), "Predictor is not a pipeline ensemble predictor"); var summaries = new IDataView[ensemble.PredictorModels.Length]; var stats = new IDataView[ensemble.PredictorModels.Length]; for (int i = 0; i < ensemble.PredictorModels.Length; i++) { var pm = ensemble.PredictorModels[i]; pm.PrepareData(host, new EmptyDataView(host, pm.TransformModel.InputSchema), out rmd, out IPredictor pred); summaries[i] = SummarizePredictor.GetSummaryAndStats(host, pred, rmd.Schema, out stats[i]); } return(new SummaryOutput() { Summaries = summaries, Stats = stats }); }