41Env.ComponentCatalog.RegisterAssembly(typeof(ExponentialAverageTransform).Assembly); 47var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 48return EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 67var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 68return EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 91var splitOutput = TrainTestSplit.Split(Env, new TrainTestSplit.Input { Data = dataView, Fraction = 0.9f }); 118dataView = Env.CreateTransform("Term{col=F1}", dataView); 119var result = FeatureCombiner.PrepareFeatures(Env, new FeatureCombiner.FeatureCombinerInput() { Data = dataView, Features = new[] { "F1", "F2", "Rest" } }).OutputData; 120var expected = Env.CreateTransform("Convert{col=F2 type=R4}", dataView); 121expected = Env.CreateTransform("KeyToValue{col=F1}", expected); 122expected = Env.CreateTransform("Term{col=F1}", expected); 123expected = Env.CreateTransform("KeyToVector{col=F1}", expected); 124expected = Env.CreateTransform("Concat{col=Features:F1,F2,Rest}", expected); 126expected = Env.CreateTransform("SelectColumns{keepcol=Features hidden=-}", expected); 127result = Env.CreateTransform("SelectColumns{keepcol=Features hidden=-}", result); 136dataView = Env.CreateTransform("Term{col=F1}", dataView); 137var trainData = FeatureCombiner.PrepareFeatures(Env, new FeatureCombiner.FeatureCombinerInput() { Data = dataView, Features = new[] { "F1", "F2", "Rest" } }); 138var lrModel = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, new LbfgsLogisticRegressionBinaryTrainer.Options { TrainingData = trainData.OutputData }).PredictorModel; 139var model = ModelOperations.CombineTwoModels(Env, new ModelOperations.SimplePredictorModelInput() { TransformModel = trainData.Model, PredictorModel = lrModel }).PredictorModel; 141var scored1 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = dataView, PredictorModel = model }).ScoredData; 142scored1 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored1, ExtraColumns = new[] { "Label" } }).OutputData; 144var scored2 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = dataView, PredictorModel = lrModel.Apply(Env, trainData.Model) }).ScoredData; 145scored2 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored2, ExtraColumns = new[] { "Label" } }).OutputData; 157dataView = Env.CreateTransform("Term{col=F1}", dataView); 159var data1 = FeatureCombiner.PrepareFeatures(Env, new FeatureCombiner.FeatureCombinerInput() { Data = dataView, Features = new[] { "F1", "F2", "Rest" } }); 160var data2 = ModelOperations.Apply(Env, new ModelOperations.ApplyTransformModelInput() { Data = dataView, TransformModel = data1.Model }); 239var catalog = Env.ComponentCatalog; 267var catalog = Env.ComponentCatalog; 328Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 329Env.ComponentCatalog.RegisterAssembly(typeof(TensorFlowTransformer).Assembly); 330Env.ComponentCatalog.RegisterAssembly(typeof(ImageLoadingTransformer).Assembly); 331Env.ComponentCatalog.RegisterAssembly(typeof(SymbolicSgdLogisticRegressionBinaryTrainer).Assembly); 332Env.ComponentCatalog.RegisterAssembly(typeof(SaveOnnxCommand).Assembly); 333Env.ComponentCatalog.RegisterAssembly(typeof(TimeSeriesProcessingEntryPoints).Assembly); 334Env.ComponentCatalog.RegisterAssembly(typeof(ParquetLoader).Assembly); 336var catalog = Env.ComponentCatalog; 350var manifest = JsonManifestUtils.BuildAllManifests(Env, catalog); 366var catalog = Env.ComponentCatalog; 368InputBuilder ib1 = new InputBuilder(Env, typeof(LbfgsLogisticRegressionBinaryTrainer.Options), catalog); 420var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 433predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 435ScoreModel.Score(Env, 438individualScores[i] = new ColumnCopyingTransformer(Env, ( 443individualScores[i] = new ColumnSelectingTransformer(Env, null, new[] { AnnotationUtils.Const.ScoreValueKind.Score }).Transform(individualScores[i]); 447var avgEnsemble = EnsembleCreator.CreateBinaryEnsemble(Env, avgEnsembleInput).PredictorModel; 449ScoreModel.Score(Env, 453var medEnsemble = EnsembleCreator.CreateBinaryEnsemble(Env, medEnsembleInput).PredictorModel; 455ScoreModel.Score(Env, 459var regEnsemble = EnsembleCreator.CreateRegressionEnsemble(Env, regEnsembleInput).PredictorModel; 461ScoreModel.Score(Env, 464var zippedScores = ZipDataView.Create(Env, individualScores); 466var avgComb = new Average(Env).GetCombiner(); 467var medComb = new Median(Env).GetCombiner(); 556var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 559var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 614var cmd = new ExecuteGraphCommand(Env, args); 742var cmd = new ExecuteGraphCommand(Env, args); 890var cmd = new ExecuteGraphCommand(Env, args); 1051var cmd = new ExecuteGraphCommand(Env, args); 1194var cmd = new ExecuteGraphCommand(Env, args); 1341var cmd = new ExecuteGraphCommand(Env, args); 1438var cmd = new ExecuteGraphCommand(Env, args); 1509var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = 3 }); 1511var lrModel = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, new LbfgsLogisticRegressionBinaryTrainer.Options { TrainingData = splitOutput.TestData[0] }).PredictorModel; 1512var calibratedLrModel = Calibrate.FixedPlatt(Env, 1515var scored1 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = lrModel }).ScoredData; 1516scored1 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored1, ExtraColumns = new[] { "Label" } }).OutputData; 1518var scored2 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = calibratedLrModel }).ScoredData; 1519scored2 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored2, ExtraColumns = new[] { "Label" } }).OutputData; 1525calibratedLrModel = Calibrate.Platt(Env, input).PredictorModel; 1526calibratedLrModel = Calibrate.Naive(Env, input).PredictorModel; 1527calibratedLrModel = Calibrate.Pav(Env, input).PredictorModel; 1530var fastForest = new FastForestBinaryTrainer(Env, "Label", "Features"); 1532var ffModel = new PredictorModelImpl(Env, rmd, splitOutput.TrainData[0], fastForest.Train(rmd)); 1533var calibratedFfModel = Calibrate.Platt(Env, 1535var twiceCalibratedFfModel = Calibrate.Platt(Env, 1537var scoredFf = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = twiceCalibratedFfModel }).ScoredData; 1559var data = new EmptyDataView(Env, schema.ToSchema()); 1560return new PredictorModelImpl(Env, new RoleMappedData(data, label: "Label", feature: null), 1561data, new PriorModelParameters(Env, 0.5f)); 1567Assert.NotNull(SchemaBindablePipelineEnsembleBase.Create(Env, models, new Average(Env), 1573SchemaBindablePipelineEnsembleBase.Create(Env, models, new Average(Env), 1585var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 1591data = new ApproximatedKernelMappingEstimator(Env, new[] { 1596data = new ColumnConcatenatingTransformer(Env, "Features", new[] { "Features1", "Features2" }).Transform(data); 1597data = new ValueToKeyMappingEstimator(Env, "Label", "Label", keyOrdinality: ValueToKeyMappingEstimator.KeyOrdinality.ByValue).Fit(data).Transform(data); 1606predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 1607var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 1609predictorModels[i] = ModelOperations.CombineTwoModels(Env, 1614ScoreModel.Score(Env, 1619var binaryEnsembleModel = EnsembleCreator.CreateBinaryPipelineEnsemble(Env, 1625var binaryEnsembleCalibrated = Calibrate.Platt(Env, 1631var binaryScored = ScoreModel.Score(Env, 1637var binaryScoredCalibrated = ScoreModel.Score(Env, 1644var regressionEnsembleModel = EnsembleCreator.CreateRegressionPipelineEnsemble(Env, 1650var regressionScored = ScoreModel.Score(Env, 1657var anomalyEnsembleModel = EnsembleCreator.CreateAnomalyPipelineEnsemble(Env, 1663var anomalyScored = ScoreModel.Score(Env, 1697using (var file = Env.CreateOutputFile(modelPath)) 1699regressionEnsembleModel.Save(Env, strm); 1702using (var file = Env.OpenInputFile(modelPath)) 1704loadedFromSaved = new PredictorModelImpl(Env, strm); 1706var scoredFromSaved = ScoreModel.Score(Env, 1755var c = new Average(Env).GetCombiner(); 1809var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 1810var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 1833dataView = LambdaColumnMapper.Create(Env, "TextToBinaryLabel", dataView, "Label", "Label", 1837var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 1845data = new TextFeaturizingEstimator(Env, "Features", new List<string> { "Text" }, 1853data = WordHashBagProducingTransformer.Create(Env, 1872predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 1873var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 1875predictorModels[i] = ModelOperations.CombineTwoModels(Env, 1880ScoreModel.Score(Env, 1885var binaryEnsembleModel = EnsembleCreator.CreateBinaryPipelineEnsemble(Env, 1891var binaryEnsembleCalibrated = Calibrate.Platt(Env, 1897var binaryScored = ScoreModel.Score(Env, 1903var binaryScoredCalibrated = ScoreModel.Score(Env, 1910var regressionEnsembleModel = EnsembleCreator.CreateRegressionPipelineEnsemble(Env, 1916var regressionScored = ScoreModel.Score(Env, 1924using (var file = Env.CreateOutputFile(modelPath)) 1926regressionEnsembleModel.Save(Env, strm); 1929using (var file = Env.OpenInputFile(modelPath)) 1931loadedFromSaved = new PredictorModelImpl(Env, strm); 1933var scoredFromSaved = ScoreModel.Score(Env, 1978var c = new Average(Env).GetCombiner(); 2026var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 2027var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 2042var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 2048data = new ApproximatedKernelMappingEstimator(Env, new[] { 2052data = new ColumnConcatenatingTransformer(Env, "Features", new[] { "Features1", "Features2" }).Transform(data); 2057predictorModels[i] = new PredictorModelImpl(Env, rmd, data, mlr.Train(rmd)); 2058var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 2060predictorModels[i] = ModelOperations.CombineTwoModels(Env, 2065ScoreModel.Score(Env, 2070var mcEnsembleModel = EnsembleCreator.CreateMulticlassPipelineEnsemble(Env, 2076var mcScored = ScoreModel.Score(Env, 2084using (var file = Env.CreateOutputFile(modelPath)) 2086mcEnsembleModel.Save(Env, strm); 2089using (var file = Env.OpenInputFile(modelPath)) 2091loadedFromSaved = new PredictorModelImpl(Env, strm); 2093var scoredFromSaved = ScoreModel.Score(Env, 2130var c = new MultiAverage(Env, new MultiAverage.Options()).GetCombiner(); 2169var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 2171EntryPoints.ImportTextData.TextLoader(Env, 2189var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels }); 2194data = new OneHotEncodingEstimator(Env, "Cat").Fit(data).Transform(data); 2195data = new ColumnConcatenatingTransformer(Env, new ColumnConcatenatingTransformer.ColumnOptions("Features", i % 2 == 0 ? new[] { "Features", "Cat" } : new[] { "Cat", "Features" })).Transform(data); 2206predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 2207var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 2209predictorModels[i] = ModelOperations.CombineTwoModels(Env, 2222var trainer = new FastTreeBinaryTrainer(Env, ftInput); 2227predictorModels[i] = new PredictorModelImpl(Env, rmd, splitOutput.TrainData[i], predictor); 2231var binaryEnsembleModel = EnsembleCreator.CreateBinaryPipelineEnsemble(Env, 2237var binaryEnsembleCalibrated = Calibrate.Platt(Env, 2244var summaryDataViews = PipelineEnsemble.Summarize(Env, 2250using (var ch = Env.Register("LinearPredictorSummary").Start("Save Data Views")) 2255var saver = Env.CreateSaver("Text"); 2256using (var file = Env.CreateOutputFile(summary)) 2263using (var file = Env.CreateOutputFile(stats)) 2367var cmd = new ExecuteGraphCommand(Env, args); 2417var cmd = new ExecuteGraphCommand(Env, args); 2462var cmd = new ExecuteGraphCommand(Env, args); 2508var cmd = new ExecuteGraphCommand(Env, args); 2563var cmd = new ExecuteGraphCommand(Env, args); 2566using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), outputPath)) 2678var cmd = new ExecuteGraphCommand(Env, args); 2693using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2696using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2699using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2702using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), confusionMatrixPath)) 2717using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2720using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2723using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2726using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), confusionMatrixPath)) 2741using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2744using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2747using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2812using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2815using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2818using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2829Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 2836Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 3216Env.Assert(Utils.Size(xfNames) == Utils.Size(xfArgs)); 3298var cmd = new ExecuteGraphCommand(Env, args); 3367var cmd = new ExecuteGraphCommand(Env, args); 3374var catalog = Env.ComponentCatalog; 3377var inputBuilder = new InputBuilder(Env, info.InputType, catalog); 3431var catalog = Env.ComponentCatalog; 3434var inputBuilder = new InputBuilder(Env, info.InputType, catalog); 3547var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3550var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 3642var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3645var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 3747var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3750var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 3908var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3911var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4099var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 4102var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4186var graph = new EntryPointGraph(Env, graphJson[FieldNames.Nodes] as JArray); 4189var runner = new GraphRunner(Env, nodes); 4192var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4245var graph = new EntryPointGraph(Env, graphJson[FieldNames.Nodes] as JArray); 4263graph = new EntryPointGraph(Env, serNodes); 4271var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4273var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 4297var model = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 4306var mcModel = LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, mcLrInput).PredictorModel; 4308var output = SummarizePredictor.Summarize(Env, 4311var mcOutput = SummarizePredictor.Summarize(Env, 4314using (var ch = Env.Register("LinearPredictorSummary").Start("Save Data Views")) 4317var saver = Env.CreateSaver("Text"); 4318using (var file = Env.CreateOutputFile(weights)) 4322using (var file = Env.CreateOutputFile(stats)) 4326using (var file = Env.CreateOutputFile(weights)) 4330using (var file = Env.CreateOutputFile(stats)) 4345using (var inputFile = new SimpleFileHandle(Env, dataPath, false, false)) 4347var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 4367var model = RandomizedPcaTrainer.TrainPcaAnomaly(Env, pcaInput).PredictorModel; 4369var output = SummarizePredictor.Summarize(Env, 4372using (var ch = Env.Register("PcaPredictorSummary").Start("Save Data Views")) 4375var saver = Env.CreateSaver("Text"); 4376using (var file = Env.CreateOutputFile(weights)) 4455var cmd = new ExecuteGraphCommand(Env, args); 4458using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), outputPath)) 4483var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4485var dataView = EntryPoints.ImportTextData.ImportText(Env, new EntryPoints.ImportTextData.Input { InputFile = inputFile }).Data; 4487var cat = Categorical.CatTransformDict(Env, new OneHotEncodingTransformer.Options() 4492var concat = SchemaManipulation.ConcatColumns(Env, new ColumnConcatenatingTransformer.Options() 4498var fastTree = Trainers.FastTree.FastTree.TrainBinary(Env, new FastTreeBinaryTrainer.Options 4507var combine = ModelOperations.CombineModels(Env, new ModelOperations.PredictorModelInput() 4513var treeLeaf = TreeFeaturize.Featurizer(Env, new TreeEnsembleFeaturizerTransform.ArgumentsForEntryPoint 4561var inputFile = new SimpleFileHandle(Env, dataFile, false, false); 4562var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 4575var embedding = Transforms.Text.TextAnalytics.WordEmbeddings(Env, new WordEmbeddingTransformer.Options() 4880var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 4881var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5032var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5033var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5206var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5207var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5390var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5391var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5618var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5619var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5798var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5799var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6097var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6098var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6317var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6318var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6489var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6490var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6515Env.ComponentCatalog.RegisterAssembly(typeof(TensorFlowTransformer).Assembly); 6531Env.ComponentCatalog.RegisterAssembly(typeof(TensorFlowTransformer).Assembly); 6606var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6607var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6697var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6698var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6714Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 6913var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6914var inputFile = new SimpleFileHandle(Env, dataPath, false, false);

67var dataView = DataViewConstructionUtils.CreateFromList(Env, 159TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 161var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

202TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 204var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms); 1080using (var file = new SimpleFileHandle(Env, tempPath, true, true))

38InitializeEnvironment(Env); 674IModelCombiner combiner = new TreeEnsembleCombiner(Env, PredictionKind.BinaryClassification); 679var scored = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = new PredictorModelImpl(Env, data, idv, fastTree) }).ScoredData; 694scoredArray[i] = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = fastTrees[i] }).ScoredData; 812LightGbm.TrainMulticlass(Env, new LightGbmMulticlassTrainer.Options 820LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options() 828LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options() 844Env, typeof(SignatureModelCombiner), name, options, predictionKind); 849var scored = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = new PredictorModelImpl(Env, data, idv, predictor) }).ScoredData; 870scoredArray[i] = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = predictors[i] }).ScoredData;

156ArrayDataViewBuilder builder = new ArrayDataViewBuilder(Env); 178using (Transposer trans = Transposer.Create(Env, view, false, names)) 203using (Transposer trans = Transposer.Create(Env, view, true, 3, 5, 4)) 222ArrayDataViewBuilder builder = new ArrayDataViewBuilder(Env); 244TransposeSaver saver = new TransposeSaver(Env, new TransposeSaver.Arguments()); 248TransposeLoader loader = new TransposeLoader(Env, new TransposeLoader.Arguments(), src);

130TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 132var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

303int result = ResultProcessor.Main(Env, args.ToArray());

16Env.ComponentCatalog.RegisterAssembly(typeof(ParquetLoader).Assembly);

17Env.ComponentCatalog.RegisterAssembly(typeof(ParquetLoader).Assembly);

821bool tmp = CmdParser.ParseArguments(Env, 833IDataView view2 = TextLoader.Create(Env, argsText, new MultiFileSource(dataPath)); 836tmp = CmdParser.ParseArguments(Env, 847view2 = TypeConvertingTransformer.Create(Env, argsConv, view2); 850tmp = CmdParser.ParseArguments(Env, 854view2 = TypeConvertingTransformer.Create(Env, argsConv, view2); 1056using (var file = Env.OpenInputFile(modelPath)) 1111var builder = new ArrayDataViewBuilder(Env); 1116var hashTransform = new HashingTransformer(Env, new HashingEstimator.ColumnOptions("F1", "F1", 5, 42)).Transform(srcView); 1132var builder = new ArrayDataViewBuilder(Env); 1139var builder = new ArrayDataViewBuilder(Env); 1147var hashTransform = new HashingTransformer(Env, new HashingEstimator.ColumnOptions("F1V", "F1V", 5, 42)).Transform(srcView); 1167ArrayDataViewBuilder builder = new ArrayDataViewBuilder(Env); 1243SaveLoadText(view, Env); 1244SaveLoad(view, Env); 1246SaveLoadText(view, Env, suffix: "NoSchema", roundTrip: false, outputSchema: false, outputHeader: true); 1247SaveLoadText(view, Env, suffix: "NoHeader", roundTrip: false, outputSchema: true, outputHeader: false); 1248SaveLoadText(view, Env, suffix: "NoSchemaNoHeader", roundTrip: false, outputSchema: false, outputHeader: false); 1250SaveLoadTransposed(view, Env); 1251SaveLoadTransposed(view, Env, suffix: "2ndSave"); 1259ArrayDataViewBuilder builder = new ArrayDataViewBuilder(Env); 1265SaveLoadText(view, Env); 1266SaveLoad(view, Env); 1274ArrayDataViewBuilder builder = new ArrayDataViewBuilder(Env); 1281SaveLoadText(view, Env); 1289SaveLoad(view, Env); 1297ArrayDataViewBuilder builder = new ArrayDataViewBuilder(Env); 1304SaveLoadText(view, Env); 1312SaveLoad(view, Env); 1536var builder = new ArrayDataViewBuilder(Env); 1592var builder = new ArrayDataViewBuilder(Env);

185Contracts.AssertValue(Env); 332if (!CmdParser.ParseArguments(Env, str, args)) 355CmdParser.ParseArguments(Env, str, a1); 358string exp1 = CmdParser.GetSettings(Env, a1, def, SettingsFlags.Default | SettingsFlags.NoUnparse); 359string cust = CmdParser.GetSettings(Env, a1, def); 363CmdParser.ParseArguments(Env, cust, a2); 364string exp2 = CmdParser.GetSettings(Env, a2, def, SettingsFlags.Default | SettingsFlags.NoUnparse); 416if (!CmdParser.ParseArguments(Env, argsLoader, args)) 440using (var file = Env.CreateOutputFile(pathModel)) 442using (var rep = RepositoryWriter.CreateNew(strm, Env)) 460using (var file = Env.OpenInputFile(pathModel))

537using (var file = Env.OpenInputFile(model.Path))

27using (var ch = Env.Start("save"))

118? new NaiveCalibrator(Env, min: -4, binSize: 4, binProbs: new[] { 0.125f, 0.875f }) 119: new PlattCalibrator(Env, slope: -0.75, offset: 0.25); 148var calibrator = new PlattCalibrator(Env, slope: -0.75, offset: 0.25); 168var calibrator = new PlattCalibrator(Env, slope: double.NaN, offset: 0.25); 181return new LinearBinaryModelParameters(Env, new VBuffer<float>(1, new[] { 2f }), bias: -0.5f); 184return new GamBinaryModelParameters(Env, 204return new FastTreeBinaryModelParameters(Env, ensemble, featureCount: 1, innerArgs: null); 206return new FastForestBinaryModelParameters(Env, ensemble, featureCount: 1, innerArgs: null); 208return new LightGbmBinaryModelParameters(Env, ensemble, featureCount: 1, innerArgs: null); 216LinearBinaryModelParameters linear => new ParameterMixingCalibratedModelParameters<LinearBinaryModelParameters, PlattCalibrator>(Env, linear, calibrator), 217GamBinaryModelParameters gam => new ValueMapperCalibratedModelParameters<GamBinaryModelParameters, PlattCalibrator>(Env, gam, calibrator), 218FastTreeBinaryModelParameters fastTree => new FeatureWeightsCalibratedModelParameters<FastTreeBinaryModelParameters, PlattCalibrator>(Env, fastTree, calibrator), 219FastForestBinaryModelParameters fastForest => new FeatureWeightsCalibratedModelParameters<FastForestBinaryModelParameters, PlattCalibrator>(Env, fastForest, calibrator), 220LightGbmBinaryModelParameters lightGbm => new FeatureWeightsCalibratedModelParameters<LightGbmBinaryModelParameters, PlattCalibrator>(Env, lightGbm, calibrator), 228using (var writer = RepositoryWriter.CreateNew(stream, Env, useFileSystem: false)) 237using var reader = RepositoryReader.Open(stream, Env, useFileSystem: false); 242Env, out var subModel, reader, Path.Combine("Predictor", "Predictor")); 245Env, out var calibrator, reader, Path.Combine("Predictor", "Calibrator")); 249ModelLoadContext.LoadModel<IPredictorProducing<float>, SignatureLoadModel>(Env, out var loaded, reader, "Predictor"); 283var builder = new ArrayDataViewBuilder(Env); 286var bindable = ScoreUtils.GetSchemaBindableMapper(Env, model); 288bindable.Bind(Env, new RoleMappedSchema(data.Schema, label: null, feature: "Features"))); 351var bldr = new ArrayDataViewBuilder(Env);

50Env.ComponentCatalog.RegisterAssembly(typeof(TestFuncs1).Assembly); 181LambdaBinder.Run(Env, ref errors, node, msg => wr.WriteLine(msg));

240using (var ch = Env.Start("save")) 305var bldr = new ArrayDataViewBuilder(Env);

707var cmd = new ExecuteGraphCommand(Env, args); 738Env.ComponentCatalog.RegisterAssembly(typeof(OnnxExportExtensions).Assembly); 742cmd = new ExecuteGraphCommand(Env, args); 1078var pipeline = new HashingEstimator(Env, "Value", useOrderedHashing: useOrderedHashing, numberOfBits: numberOfBits); 1129var pipeline = new HashingEstimator(Env, "Value", useOrderedHashing: false, numberOfBits: numberOfBits); 2273using (var file = Env.CreateOutputFile(binaryFormatPath)) 2279using (var file = Env.CreateOutputFile(textFormatPath))

848var bldr = new ArrayDataViewBuilder(Env); 929var bldr = new ArrayDataViewBuilder(Env);

52CheckSameValues(ColumnSelectingTransformer.CreateDrop(Env, data, "Comment"), 53ColumnSelectingTransformer.CreateDrop(Env, expectedData, "Comment"), checkId: false);

83using (var ch = Env.Start("save")) 102var pipe = new ValueToKeyMappingEstimator(Env, new[]{ 117var est = new ValueToKeyMappingEstimator(Env, new[]{ 127TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 129var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms); 139var termEst = new ValueToKeyMappingEstimator(Env, new[] {

24var plattCalibratorEstimator = new PlattCalibratorEstimator(Env); 45var fixedPlattCalibratorEstimator = new FixedPlattCalibratorEstimator(Env); 65var naiveCalibratorEstimator = new NaiveCalibratorEstimator(Env); 85var pavCalibratorEstimator = new IsotonicCalibratorEstimator(Env); 181var calibratorPlattEstimator = new PlattCalibratorEstimator(Env, 187var calibratorFixedPlattEstimator = new FixedPlattCalibratorEstimator(Env, 193var calibratorNaiveEstimator = new NaiveCalibratorEstimator(Env, 199var calibratorIsotonicEstimator = new IsotonicCalibratorEstimator(Env, 262var newPlattCalibratorEstimator = new PlattCalibratorEstimator(Env);

68var data = new TextLoader(Env, GetFafmBCLoaderArgs())

148var result = ModelFileUtils.LoadPredictorOrNull(Env, fs) as CalibratedModelParametersBase<LinearBinaryModelParameters, PlattCalibrator>; 239var result = ModelFileUtils.LoadPredictorOrNull(Env, fs) as MaximumEntropyModelParameters;

32var data = new TextLoader(Env, GetLoaderArgs(labelColumnName, matrixColumnIndexColumnName, matrixRowIndexColumnName)) 36var invalidData = new TextLoader(Env, GetLoaderArgs(labelColumnName, matrixColumnIndexColumnName + "Renamed", matrixRowIndexColumnName + "Renamed")) 539using (var ch = Env.Start("load"))

25var calibrator = new PlattCalibratorEstimator(Env); 33.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 50.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 83var loader = new TextLoader(Env, options: options); 97var pipeline = new ColumnConcatenatingEstimator(Env, "Vars", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth") 98.Append(new ValueToKeyMappingEstimator(Env, "Label")) 100.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel"));

16return new TextLoader(Env,

20var trainer = new SymbolicSgdLogisticRegressionBinaryTrainer(Env, new SymbolicSgdLogisticRegressionBinaryTrainer.Options()); 39var withInitPredictor = new SymbolicSgdLogisticRegressionBinaryTrainer(Env, new SymbolicSgdLogisticRegressionBinaryTrainer.Options()).Fit(transformedData, 43var notInitPredictor = new SymbolicSgdLogisticRegressionBinaryTrainer(Env, new SymbolicSgdLogisticRegressionBinaryTrainer.Options()).Fit(transformedData);

30var reader = new TextLoader(Env, new TextLoader.Options() 44var pipeline = new RandomizedPcaTrainer(Env, featureColumn, rank: 10, seed: 1); 59var reader = new TextLoader(Env, new TextLoader.Options 74var pipeline = new KMeansTrainer(Env, new KMeansTrainer.Options 99var pipeWithTrainer = pipe.AppendCacheCheckpoint(Env).Append(trainer); 130var pipeWithTrainer = pipe.AppendCacheCheckpoint(Env).Append(trainer); 172var pipeWithTrainer = pipe.AppendCacheCheckpoint(Env).Append(trainer); 191var data = new TextLoader(Env, 206var pipeline = new TextFeaturizingEstimator(Env, "Features", "SentimentText"); 227var data = new TextLoader(Env, new TextLoader.Options 240var pipeline = new ValueToKeyMappingEstimator(Env, new[]{ 249return new TextLoader(Env, 278var data = new TextLoader(Env, new TextLoader.Options() 288var pipeline = new ValueToKeyMappingEstimator(Env, "Label");

46var treeFeaturizer = new TreeEnsembleFeaturizerBindableMapper(Env, args, model.Model); 54var boundMapper = (treeFeaturizer as ISchemaBindableMapper).Bind(Env, roleMappedSchema); 619using (var file = new SimpleFileHandle(Env, tempPath, true, true)) 676using (var file = new SimpleFileHandle(Env, tempPath, true, true))

159var trainer = new GamBinaryTrainer(Env, new GamBinaryTrainer.Options 324var trainer = new GamRegressionTrainer(Env, new GamRegressionTrainer.Options 382.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 422.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 442.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 467.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 486.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel"));

232using (var ch = Env.Start("saving")) 235TrainUtils.SaveModel(Env, ch, ms, null, resultRoles); 237var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

328TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 330var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

44var pipe = new TokenizingByCharactersEstimator(Env, columns: new[] { ("TokenizeA", "A"), ("TokenizeB", "B") }); 62var pipe = new TokenizingByCharactersEstimator(Env, columns: new[] { ("TokenizeA", "A"), ("TokenizeB", "B") }); 67TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 69var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

87using (var ch = Env.Start("save")) 151using (var ch = Env.Start("save"))

327TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 329var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms); 393using (var ch = Env.Start("load"))

47using (var ch = Env.Start("save")) 84using (var ch = Env.Start("save")) 126using (var ch = Env.Start("save")) 159TrainUtils.SaveModel(ML, Env.Start("saving"), ms, null, resultRoles); 186using (var ch = Env.Start("save")) 219TrainUtils.SaveModel(ML, Env.Start("saving"), ms, null, resultRoles);

51var groupTransform = new GroupTransform(Env, dataView, "Age", "UserName", "Gender"); 88var ungroupTransform = new UngroupTransform(Env, dataView, UngroupTransform.UngroupMode.Inner, "UserName", "Gender");

123TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 125var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms); 140var xf = new HashingTransformer(Env, new[] { colInfo }); 341using (var ch = Env.Start("save")) 343var saver = new TextSaver(Env, new TextSaver.Arguments { Silent = true });

48dataView = new ValueToKeyMappingEstimator(Env, new[]{ 68var transformedData = new ValueToKeyMappingEstimator(Env, new[] { 92var termEst = new ValueToKeyMappingEstimator(Env, new[] { 148var est = new ValueToKeyMappingEstimator(Env, new[]{ 160TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 162var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

27var reader = new TextLoader(Env, new TextLoader.Options 39data = new ValueToKeyMappingEstimator(Env, new[] { 43var badData1 = new ColumnCopyingTransformer(Env, ("A", "BareKey")).Transform(data); 44var badData2 = new ColumnCopyingTransformer(Env, ("B", "VectorString")).Transform(data); 46var est = new KeyToValueMappingEstimator(Env, ("A_back", "A"), ("B_back", "B")); 52using (var ch = Env.Start("save")) 54var saver = new TextSaver(Env, new TextSaver.Arguments { Silent = true }); 73var transformedData = new ValueToKeyMappingEstimator(Env, new[] {

55dataView = new ValueToKeyMappingEstimator(Env, new[]{ 78var transformedData = new ValueToKeyMappingEstimator(Env, new[] { 102var termEst = new ValueToKeyMappingEstimator(Env, new[] { 207var est = new ValueToKeyMappingEstimator(Env, new[]{ 222TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 224var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

85TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 87var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

180TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 182var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

37var loader = new TextLoader(Env, new TextLoader.Options 50var est = new NormalizingEstimator(Env, 78var badData1 = new ColumnCopyingTransformer(Env, ("float1", "int1")).Transform(data); 79var badData2 = new ColumnCopyingTransformer(Env, ("float4", "float0")).Transform(data); 85using (var ch = Env.Start("save")) 87var saver = new TextSaver(Env, new TextSaver.Arguments { Silent = true }); 106var loader = new TextLoader(Env, new TextLoader.Options 119var est = new NormalizingEstimator(Env, 471var loader = new TextLoader(Env, new TextLoader.Options 481var est1 = new NormalizingEstimator(Env, "float4"); 482var est2 = new NormalizingEstimator(Env, NormalizingEstimator.NormalizationMode.MinMax, ("float4", "float4")); 483var est3 = new NormalizingEstimator(Env, new NormalizingEstimator.MinMaxColumnOptions("float4")); 503var est6 = new NormalizingEstimator(Env, NormalizingEstimator.NormalizationMode.MeanVariance, ("float4", "float4")); 504var est7 = new NormalizingEstimator(Env, new NormalizingEstimator.MeanVarianceColumnOptions("float4")); 516var est9 = new NormalizingEstimator(Env, NormalizingEstimator.NormalizationMode.LogMeanVariance, ("float4", "float4")); 517var est10 = new NormalizingEstimator(Env, new NormalizingEstimator.LogMeanVarianceColumnOptions("float4")); 529var est12 = new NormalizingEstimator(Env, NormalizingEstimator.NormalizationMode.Binning, ("float4", "float4")); 530var est13 = new NormalizingEstimator(Env, new NormalizingEstimator.BinningColumnOptions("float4")); 542var est15 = new NormalizingEstimator(Env, NormalizingEstimator.NormalizationMode.SupervisedBinning, ("float4", "float4")); 543var est16 = new NormalizingEstimator(Env, new NormalizingEstimator.SupervisedBinningColumOptions("float4")); 555var est18 = new NormalizingEstimator(Env, NormalizingEstimator.NormalizationMode.RobustScaling, ("float4", "float4")); 556var est19 = new NormalizingEstimator(Env, new NormalizingEstimator.RobustScalingColumnOptions("float4")); 575var loader = new TextLoader(Env, new TextLoader.Options 633var loader = new TextLoader(Env, new TextLoader.Options 672using (var ch = Env.Start("save")) 706using (var ch = Env.Start("save")) 743TrainUtils.SaveModel(ML, Env.Start("saving"), ms, null, resultRoles); 769using (var ch = Env.Start("save")) 804TrainUtils.SaveModel(ML, Env.Start("saving"), ms, null, resultRoles); 829using (var ch = Env.Start("save")) 864TrainUtils.SaveModel(ML, Env.Start("saving"), ms, null, resultRoles); 878var result = ModelFileUtils.LoadTransforms(Env, dataView, fs); 991var loader = new TextLoader(Env, new TextLoader.Options 1009using (var ch = Env.Start("save")) 1011var saver = new TextSaver(Env, new TextSaver.Arguments { Silent = true });

108TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 110var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

49var est = ColumnSelectingEstimator.KeepColumns(Env, "A", "C"); 70var est = ColumnSelectingEstimator.KeepColumns(Env, "C", "A"); 89var est = ColumnSelectingEstimator.DropColumns(Env, "A", "C"); 124var est = ColumnSelectingEstimator.KeepColumns(Env, "D", "G"); 133var est = new ColumnCopyingEstimator(Env, new[] { ("A", "A"), ("B", "B") }); 134var chain = est.Append(ColumnSelectingEstimator.KeepColumns(Env, "C", "A")); 156var est = new ColumnCopyingEstimator(Env, new[] { ("A", "A"), ("B", "B") }); 179var est = ColumnSelectingEstimator.KeepColumns(Env, "A", "B"); 198var est = new ColumnCopyingEstimator(Env, new[] { ("A", "A"), ("B", "B") }).Append( 223var result = ModelFileUtils.LoadTransforms(Env, dataView, fs); 251var result = ModelFileUtils.LoadTransforms(Env, dataView, fs); 279var result = ModelFileUtils.LoadTransforms(Env, dataView, fs); 307var result = ModelFileUtils.LoadTransforms(Env, dataView, fs);

494var est = new WordTokenizingEstimator(Env, "words", "text", separators: new[] { ' ', '?', '!', '.', ',' }); 498var saver = new TextSaver(Env, new TextSaver.Arguments { Silent = true }); 500using (var ch = Env.Start("save")) 662var result = ModelFileUtils.LoadTransforms(Env, data, fs); 721var builder = new ArrayDataViewBuilder(Env);

82var pipe = new TextNormalizingEstimator(Env, columns: new[] { ("NormA", "A"), ("NormB", "B") }); 88TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 90var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

58var lookupMap = DataViewHelper.CreateDataView(Env, keys, values, 62var estimator = new ValueMappingEstimator<string, int>(Env, lookupMap, 96var lookupMap = DataViewHelper.CreateDataView(Env, keys, values, 100var valueMappingEstimator = new ValueMappingEstimator<string, int>(Env, lookupMap, 105var estimator = new WordTokenizingEstimator(Env, new[]{ 145var estimator = new WordTokenizingEstimator(Env, new[] { new WordTokenizingEstimator.ColumnOptions("TokenizeA", "A") }). 180var lookupMap = DataViewHelper.CreateDataView(Env, keys, values, 184var estimator = new ValueMappingEstimator<string, int>(Env, lookupMap, 236var estimator = new ValueMappingEstimator(Env, mapView, mapView.Schema["Key"], mapView.Schema["Value"], new[] { ("D", "A"), ("E", "B"), ("F", "C") }); 269var lookupMap = DataViewHelper.CreateDataView(Env, keys, values, 273var estimator = new ValueMappingEstimator<string, int>(Env, lookupMap, 310var lookupMap = DataViewHelper.CreateDataView(Env, keys, values, 314var estimator = new ValueMappingEstimator<string, int>(Env, lookupMap, 348var lookupMap = DataViewHelper.CreateDataView(Env, keys, values, 352Assert.Throws<InvalidOperationException>(() => new ValueMappingEstimator<string, int>(Env, lookupMap, 719var result = ModelFileUtils.LoadTransforms(Env, dataView, fs); 736var result = ModelFileUtils.LoadTransforms(Env, dataView, fs);

58var pipe = new WordTokenizingEstimator(Env, new[]{ 100var pipe = new WordTokenizingEstimator(Env, new[]{ 108TrainUtils.SaveModel(Env, Env.Start("saving"), ms, null, resultRoles); 110var loadedView = ModelFileUtils.LoadTransforms(Env, dataView, ms);

20Env.ComponentCatalog.RegisterAssembly(typeof(ExponentialAverageTransform).Assembly);

63var pipe = new SsaChangePointEstimator(Env, "Change", 98var pipe = new SsaForecastingEstimator(Env, "Forecast", "Value", 10, 11, 22, 4, 133var pipe = new SsaSpikeEstimator(Env, "Change", 160var pipe = new IidChangePointEstimator(Env, 187var pipe = new IidSpikeEstimator(Env,