40Env.ComponentCatalog.RegisterAssembly(typeof(ExponentialAverageTransform).Assembly); 46var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 47return EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 66var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 67return EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 90var splitOutput = TrainTestSplit.Split(Env, new TrainTestSplit.Input { Data = dataView, Fraction = 0.9f }); 117dataView = Env.CreateTransform("Term{col=F1}", dataView); 118var result = FeatureCombiner.PrepareFeatures(Env, new FeatureCombiner.FeatureCombinerInput() { Data = dataView, Features = new[] { "F1", "F2", "Rest" } }).OutputData; 119var expected = Env.CreateTransform("Convert{col=F2 type=R4}", dataView); 120expected = Env.CreateTransform("KeyToValue{col=F1}", expected); 121expected = Env.CreateTransform("Term{col=F1}", expected); 122expected = Env.CreateTransform("KeyToVector{col=F1}", expected); 123expected = Env.CreateTransform("Concat{col=Features:F1,F2,Rest}", expected); 125expected = Env.CreateTransform("SelectColumns{keepcol=Features hidden=-}", expected); 126result = Env.CreateTransform("SelectColumns{keepcol=Features hidden=-}", result); 135dataView = Env.CreateTransform("Term{col=F1}", dataView); 136var trainData = FeatureCombiner.PrepareFeatures(Env, new FeatureCombiner.FeatureCombinerInput() { Data = dataView, Features = new[] { "F1", "F2", "Rest" } }); 137var lrModel = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, new LbfgsLogisticRegressionBinaryTrainer.Options { TrainingData = trainData.OutputData }).PredictorModel; 138var model = ModelOperations.CombineTwoModels(Env, new ModelOperations.SimplePredictorModelInput() { TransformModel = trainData.Model, PredictorModel = lrModel }).PredictorModel; 140var scored1 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = dataView, PredictorModel = model }).ScoredData; 141scored1 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored1, ExtraColumns = new[] { "Label" } }).OutputData; 143var scored2 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = dataView, PredictorModel = lrModel.Apply(Env, trainData.Model) }).ScoredData; 144scored2 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored2, ExtraColumns = new[] { "Label" } }).OutputData; 156dataView = Env.CreateTransform("Term{col=F1}", dataView); 158var data1 = FeatureCombiner.PrepareFeatures(Env, new FeatureCombiner.FeatureCombinerInput() { Data = dataView, Features = new[] { "F1", "F2", "Rest" } }); 159var data2 = ModelOperations.Apply(Env, new ModelOperations.ApplyTransformModelInput() { Data = dataView, TransformModel = data1.Model }); 238var catalog = Env.ComponentCatalog; 266var catalog = Env.ComponentCatalog; 327Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 328Env.ComponentCatalog.RegisterAssembly(typeof(TensorFlowTransformer).Assembly); 329Env.ComponentCatalog.RegisterAssembly(typeof(ImageLoadingTransformer).Assembly); 330Env.ComponentCatalog.RegisterAssembly(typeof(SymbolicSgdLogisticRegressionBinaryTrainer).Assembly); 331Env.ComponentCatalog.RegisterAssembly(typeof(SaveOnnxCommand).Assembly); 332Env.ComponentCatalog.RegisterAssembly(typeof(TimeSeriesProcessingEntryPoints).Assembly); 333Env.ComponentCatalog.RegisterAssembly(typeof(ParquetLoader).Assembly); 335var catalog = Env.ComponentCatalog; 349var manifest = JsonManifestUtils.BuildAllManifests(Env, catalog); 365var catalog = Env.ComponentCatalog; 367InputBuilder ib1 = new InputBuilder(Env, typeof(LbfgsLogisticRegressionBinaryTrainer.Options), catalog); 419var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 432predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 434ScoreModel.Score(Env, 437individualScores[i] = new ColumnCopyingTransformer(Env, ( 442individualScores[i] = new ColumnSelectingTransformer(Env, null, new[] { AnnotationUtils.Const.ScoreValueKind.Score }).Transform(individualScores[i]); 446var avgEnsemble = EnsembleCreator.CreateBinaryEnsemble(Env, avgEnsembleInput).PredictorModel; 448ScoreModel.Score(Env, 452var medEnsemble = EnsembleCreator.CreateBinaryEnsemble(Env, medEnsembleInput).PredictorModel; 454ScoreModel.Score(Env, 458var regEnsemble = EnsembleCreator.CreateRegressionEnsemble(Env, regEnsembleInput).PredictorModel; 460ScoreModel.Score(Env, 463var zippedScores = ZipDataView.Create(Env, individualScores); 465var avgComb = new Average(Env).GetCombiner(); 466var medComb = new Median(Env).GetCombiner(); 555var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 558var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 613var cmd = new ExecuteGraphCommand(Env, args); 741var cmd = new ExecuteGraphCommand(Env, args); 889var cmd = new ExecuteGraphCommand(Env, args); 1050var cmd = new ExecuteGraphCommand(Env, args); 1193var cmd = new ExecuteGraphCommand(Env, args); 1340var cmd = new ExecuteGraphCommand(Env, args); 1437var cmd = new ExecuteGraphCommand(Env, args); 1508var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = 3 }); 1510var lrModel = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, new LbfgsLogisticRegressionBinaryTrainer.Options { TrainingData = splitOutput.TestData[0] }).PredictorModel; 1511var calibratedLrModel = Calibrate.FixedPlatt(Env, 1514var scored1 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = lrModel }).ScoredData; 1515scored1 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored1, ExtraColumns = new[] { "Label" } }).OutputData; 1517var scored2 = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = calibratedLrModel }).ScoredData; 1518scored2 = ScoreModel.SelectColumns(Env, new ScoreModel.ScoreColumnSelectorInput() { Data = scored2, ExtraColumns = new[] { "Label" } }).OutputData; 1524calibratedLrModel = Calibrate.Platt(Env, input).PredictorModel; 1525calibratedLrModel = Calibrate.Naive(Env, input).PredictorModel; 1526calibratedLrModel = Calibrate.Pav(Env, input).PredictorModel; 1529var fastForest = new FastForestBinaryTrainer(Env, "Label", "Features"); 1531var ffModel = new PredictorModelImpl(Env, rmd, splitOutput.TrainData[0], fastForest.Train(rmd)); 1532var calibratedFfModel = Calibrate.Platt(Env, 1534var twiceCalibratedFfModel = Calibrate.Platt(Env, 1536var scoredFf = ScoreModel.Score(Env, new ScoreModel.Input() { Data = splitOutput.TestData[2], PredictorModel = twiceCalibratedFfModel }).ScoredData; 1545var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 1551data = new ApproximatedKernelMappingEstimator(Env, new[] { 1556data = new ColumnConcatenatingTransformer(Env, "Features", new[] { "Features1", "Features2" }).Transform(data); 1557data = new ValueToKeyMappingEstimator(Env, "Label", "Label", keyOrdinality: ValueToKeyMappingEstimator.KeyOrdinality.ByValue).Fit(data).Transform(data); 1566predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 1567var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 1569predictorModels[i] = ModelOperations.CombineTwoModels(Env, 1574ScoreModel.Score(Env, 1579var binaryEnsembleModel = EnsembleCreator.CreateBinaryPipelineEnsemble(Env, 1585var binaryEnsembleCalibrated = Calibrate.Platt(Env, 1591var binaryScored = ScoreModel.Score(Env, 1597var binaryScoredCalibrated = ScoreModel.Score(Env, 1604var regressionEnsembleModel = EnsembleCreator.CreateRegressionPipelineEnsemble(Env, 1610var regressionScored = ScoreModel.Score(Env, 1617var anomalyEnsembleModel = EnsembleCreator.CreateAnomalyPipelineEnsemble(Env, 1623var anomalyScored = ScoreModel.Score(Env, 1657using (var file = Env.CreateOutputFile(modelPath)) 1659regressionEnsembleModel.Save(Env, strm); 1662using (var file = Env.OpenInputFile(modelPath)) 1664loadedFromSaved = new PredictorModelImpl(Env, strm); 1666var scoredFromSaved = ScoreModel.Score(Env, 1715var c = new Average(Env).GetCombiner(); 1769var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 1770var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 1793dataView = LambdaColumnMapper.Create(Env, "TextToBinaryLabel", dataView, "Label", "Label", 1797var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 1805data = new TextFeaturizingEstimator(Env, "Features", new List<string> { "Text" }, 1813data = WordHashBagProducingTransformer.Create(Env, 1832predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 1833var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 1835predictorModels[i] = ModelOperations.CombineTwoModels(Env, 1840ScoreModel.Score(Env, 1845var binaryEnsembleModel = EnsembleCreator.CreateBinaryPipelineEnsemble(Env, 1851var binaryEnsembleCalibrated = Calibrate.Platt(Env, 1857var binaryScored = ScoreModel.Score(Env, 1863var binaryScoredCalibrated = ScoreModel.Score(Env, 1870var regressionEnsembleModel = EnsembleCreator.CreateRegressionPipelineEnsemble(Env, 1876var regressionScored = ScoreModel.Score(Env, 1884using (var file = Env.CreateOutputFile(modelPath)) 1886regressionEnsembleModel.Save(Env, strm); 1889using (var file = Env.OpenInputFile(modelPath)) 1891loadedFromSaved = new PredictorModelImpl(Env, strm); 1893var scoredFromSaved = ScoreModel.Score(Env, 1938var c = new Average(Env).GetCombiner(); 1986var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 1987var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 2002var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels + 1 }); 2008data = new ApproximatedKernelMappingEstimator(Env, new[] { 2012data = new ColumnConcatenatingTransformer(Env, "Features", new[] { "Features1", "Features2" }).Transform(data); 2017predictorModels[i] = new PredictorModelImpl(Env, rmd, data, mlr.Train(rmd)); 2018var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 2020predictorModels[i] = ModelOperations.CombineTwoModels(Env, 2025ScoreModel.Score(Env, 2030var mcEnsembleModel = EnsembleCreator.CreateMulticlassPipelineEnsemble(Env, 2036var mcScored = ScoreModel.Score(Env, 2044using (var file = Env.CreateOutputFile(modelPath)) 2046mcEnsembleModel.Save(Env, strm); 2049using (var file = Env.OpenInputFile(modelPath)) 2051loadedFromSaved = new PredictorModelImpl(Env, strm); 2053var scoredFromSaved = ScoreModel.Score(Env, 2090var c = new MultiAverage(Env, new MultiAverage.Options()).GetCombiner(); 2129var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 2131EntryPoints.ImportTextData.TextLoader(Env, 2149var splitOutput = CVSplit.Split(Env, new CVSplit.Input { Data = dataView, NumFolds = nModels }); 2154data = new OneHotEncodingEstimator(Env, "Cat").Fit(data).Transform(data); 2155data = new ColumnConcatenatingTransformer(Env, new ColumnConcatenatingTransformer.ColumnOptions("Features", i % 2 == 0 ? new[] { "Features", "Cat" } : new[] { "Cat", "Features" })).Transform(data); 2166predictorModels[i] = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 2167var transformModel = new TransformModelImpl(Env, data, splitOutput.TrainData[i]); 2169predictorModels[i] = ModelOperations.CombineTwoModels(Env, 2182var trainer = new FastTreeBinaryTrainer(Env, ftInput); 2187predictorModels[i] = new PredictorModelImpl(Env, rmd, splitOutput.TrainData[i], predictor); 2191var binaryEnsembleModel = EnsembleCreator.CreateBinaryPipelineEnsemble(Env, 2197var binaryEnsembleCalibrated = Calibrate.Platt(Env, 2204var summaryDataViews = PipelineEnsemble.Summarize(Env, 2210using (var ch = Env.Register("LinearPredictorSummary").Start("Save Data Views")) 2215var saver = Env.CreateSaver("Text"); 2216using (var file = Env.CreateOutputFile(summary)) 2223using (var file = Env.CreateOutputFile(stats)) 2327var cmd = new ExecuteGraphCommand(Env, args); 2377var cmd = new ExecuteGraphCommand(Env, args); 2422var cmd = new ExecuteGraphCommand(Env, args); 2468var cmd = new ExecuteGraphCommand(Env, args); 2523var cmd = new ExecuteGraphCommand(Env, args); 2526using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), outputPath)) 2638var cmd = new ExecuteGraphCommand(Env, args); 2653using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2656using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2659using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2662using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), confusionMatrixPath)) 2677using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2680using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2683using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2686using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), confusionMatrixPath)) 2701using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2704using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2707using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2772using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), warningsPath)) 2775using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), overallMetricsPath)) 2778using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), instanceMetricsPath)) 2789Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 2796Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 3176Env.Assert(Utils.Size(xfNames) == Utils.Size(xfArgs)); 3258var cmd = new ExecuteGraphCommand(Env, args); 3327var cmd = new ExecuteGraphCommand(Env, args); 3334var catalog = Env.ComponentCatalog; 3337var inputBuilder = new InputBuilder(Env, info.InputType, catalog); 3391var catalog = Env.ComponentCatalog; 3394var inputBuilder = new InputBuilder(Env, info.InputType, catalog); 3507var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3510var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 3602var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3605var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 3707var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3710var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 3868var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 3871var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4059var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 4062var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4146var graph = new EntryPointGraph(Env, graphJson[FieldNames.Nodes] as JArray); 4149var runner = new GraphRunner(Env, nodes); 4152var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4205var graph = new EntryPointGraph(Env, graphJson[FieldNames.Nodes] as JArray); 4223graph = new EntryPointGraph(Env, serNodes); 4231var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4233var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 4257var model = LbfgsLogisticRegressionBinaryTrainer.TrainBinary(Env, lrInput).PredictorModel; 4266var mcModel = LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, mcLrInput).PredictorModel; 4268var output = SummarizePredictor.Summarize(Env, 4271var mcOutput = SummarizePredictor.Summarize(Env, 4274using (var ch = Env.Register("LinearPredictorSummary").Start("Save Data Views")) 4277var saver = Env.CreateSaver("Text"); 4278using (var file = Env.CreateOutputFile(weights)) 4282using (var file = Env.CreateOutputFile(stats)) 4286using (var file = Env.CreateOutputFile(weights)) 4290using (var file = Env.CreateOutputFile(stats)) 4305using (var inputFile = new SimpleFileHandle(Env, dataPath, false, false)) 4307var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 4327var model = RandomizedPcaTrainer.TrainPcaAnomaly(Env, pcaInput).PredictorModel; 4329var output = SummarizePredictor.Summarize(Env, 4332using (var ch = Env.Register("PcaPredictorSummary").Start("Save Data Views")) 4335var saver = Env.CreateSaver("Text"); 4336using (var file = Env.CreateOutputFile(weights)) 4415var cmd = new ExecuteGraphCommand(Env, args); 4418using (var loader = new BinaryLoader(Env, new BinaryLoader.Arguments(), outputPath)) 4443var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4445var dataView = EntryPoints.ImportTextData.ImportText(Env, new EntryPoints.ImportTextData.Input { InputFile = inputFile }).Data; 4447var cat = Categorical.CatTransformDict(Env, new OneHotEncodingTransformer.Options() 4452var concat = SchemaManipulation.ConcatColumns(Env, new ColumnConcatenatingTransformer.Options() 4458var fastTree = Trainers.FastTree.FastTree.TrainBinary(Env, new FastTreeBinaryTrainer.Options 4467var combine = ModelOperations.CombineModels(Env, new ModelOperations.PredictorModelInput() 4473var treeLeaf = TreeFeaturize.Featurizer(Env, new TreeEnsembleFeaturizerTransform.ArgumentsForEntryPoint 4521var inputFile = new SimpleFileHandle(Env, dataFile, false, false); 4522var dataView = EntryPoints.ImportTextData.TextLoader(Env, new EntryPoints.ImportTextData.LoaderInput() 4535var embedding = Transforms.Text.TextAnalytics.WordEmbeddings(Env, new WordEmbeddingTransformer.Options() 4840var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 4841var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 4992var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 4993var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5166var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5167var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5350var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5351var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5578var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5579var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 5758var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 5759var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6057var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6058var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6277var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6278var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6449var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6450var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6475Env.ComponentCatalog.RegisterAssembly(typeof(TensorFlowTransformer).Assembly); 6491Env.ComponentCatalog.RegisterAssembly(typeof(TensorFlowTransformer).Assembly); 6566var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6567var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6657var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6658var inputFile = new SimpleFileHandle(Env, dataPath, false, false); 6674Env.ComponentCatalog.RegisterAssembly(typeof(LightGbmBinaryModelParameters).Assembly); 6873var runner = new GraphRunner(Env, graph[FieldNames.Nodes] as JArray); 6874var 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); 669IModelCombiner combiner = new TreeEnsembleCombiner(Env, PredictionKind.BinaryClassification); 674var scored = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = new PredictorModelImpl(Env, data, idv, fastTree) }).ScoredData; 689scoredArray[i] = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = fastTrees[i] }).ScoredData; 807LightGbm.TrainMulticlass(Env, new LightGbmMulticlassTrainer.Options 815LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options() 823LbfgsMaximumEntropyMulticlassTrainer.TrainMulticlass(Env, new LbfgsMaximumEntropyMulticlassTrainer.Options() 839Env, typeof(SignatureModelCombiner), name, options, predictionKind); 844var scored = ScoreModel.Score(Env, new ScoreModel.Input() { Data = idv, PredictorModel = new PredictorModelImpl(Env, data, idv, predictor) }).ScoredData; 865scoredArray[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);

301ResultProcessor.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"))

125var 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))

133var trainer = new GamBinaryTrainer(Env, new GamBinaryTrainer.Options 253var trainer = new GamRegressionTrainer(Env, new GamRegressionTrainer.Options 311.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 351.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 371.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 396.Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); 415.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,