128 references to Auto
Microsoft.ML.AutoML (11)
API\BinaryClassificationExperiment.cs (5)
155_experiment = context.Auto().CreateExperiment(); 334return preFeaturizer.Append(Context.Auto().Featurizer(trainData, columnInformation, Features)) 335.Append(Context.Auto().BinaryClassification(labelColumnName: columnInformation.LabelColumnName, useSdcaLogisticRegression: useSdca, useFastTree: useFastTree, useLgbm: useLgbm, useLbfgsLogisticRegression: uselbfgs, useFastForest: useFastForest, featureColumnName: Features)); 339return Context.Auto().Featurizer(trainData, columnInformation, Features) 340.Append(Context.Auto().BinaryClassification(labelColumnName: columnInformation.LabelColumnName, useSdcaLogisticRegression: useSdca, useFastTree: useFastTree, useLgbm: useLgbm, useLbfgsLogisticRegression: uselbfgs, useFastForest: useFastForest, featureColumnName: Features));
API\MulticlassClassificationExperiment.cs (3)
139_experiment = context.Auto().CreateExperiment(); 331pipeline = pipeline.Append(Context.Auto().Featurizer(trainData, columnInformation, Features)); 333pipeline = pipeline.Append(Context.Auto().MultiClassification(label, useSdcaMaximumEntrophy: useSdcaMaximumEntrophy, useFastTree: useFastTree, useLgbm: useLgbm, useLbfgsMaximumEntrophy: uselbfgsME, useLbfgsLogisticRegression: uselbfgsLR, useFastForest: useFastForest, featureColumnName: Features));
API\RegressionExperiment.cs (3)
134_experiment = context.Auto().CreateExperiment(); 312pipeline = pipeline.Append(Context.Auto().Featurizer(trainData, columnInformation, Features)); 313pipeline = pipeline.Append(Context.Auto().Regression(label, useSdca: useSdca, useFastTree: useFastTree, useLgbm: useLgbm, useLbfgsPoissonRegression: uselbfgs, useFastForest: useFastForest, featureColumnName: Features));
Microsoft.ML.AutoML.Samples (12)
AutoFit\BinaryClassificationExperiment.cs (1)
26ExperimentResult<BinaryClassificationMetrics> experimentResult = mlContext.Auto()
AutoFit\MulticlassClassificationExperiment.cs (1)
27ExperimentResult<MulticlassClassificationMetrics> experimentResult = mlContext.Auto()
AutoFit\RankingExperiment.cs (1)
30ExperimentResult<RankingMetrics> experimentResult = mlContext.Auto()
AutoFit\RecommendationExperiment.cs (1)
33ExperimentResult<RegressionMetrics> experimentResult = mlContext.Auto()
AutoFit\RegressionExperiment.cs (1)
27ExperimentResult<RegressionMetrics> experimentResult = mlContext.Auto()
AutoMLExperiment.cs (2)
29var pipeline = context.Auto().BinaryClassification(labelColumnName: "Label", featureColumnName: "Features"); 32var experiment = context.Auto().CreateExperiment();
Cifar10.cs (3)
37var experiment = context.Auto().CreateExperiment(); 38var pipeline = context.Auto().Featurizer(trainDataset) 39.Append(context.Auto().MultiClassification());
Sweepable\SweepableLightGBMBinaryExperiment.cs (2)
45var lgbm = context.Auto().CreateSweepableEstimator((_context, option) => 58var experiment = context.Auto().CreateExperiment();
Microsoft.ML.AutoML.Tests (103)
AutoFeaturizerTests.cs (7)
48var pipeline = context.Auto().Featurizer(dataset, outputColumnName: "OutputFeature", excludeColumns: new[] { "Label" }); 60var pipeline = context.Auto().Featurizer(dataset, excludeColumns: new[] { "Label" }); 72var pipeline = context.Auto().Featurizer(dataset, excludeColumns: new[] { DatasetUtil.NewspaperChurnLabel }); 85var pipeline = context.Auto().Featurizer(dataset, excludeColumns: new[] { "A16" }); 95var pipeline = context.Auto().ImagePathFeaturizer("imagePath", "imagePath"); 108var columnInference = context.Auto().InferColumns(datasetPath, "Label"); 111var pipeline = context.Auto().Featurizer(trainData, columnInference.ColumnInformation);
AutoFitTests.cs (30)
46var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel); 58var result = context.Auto() 72var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel); 85var result = context.Auto() 99var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel); 112var result = context.Auto() 126var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel); 137var result = context.Auto() 171var result = context.Auto() 201var result = context.Auto() 232var result = context.Auto() 241result = context.Auto() 260var columnInference = context.Auto().InferColumns(DatasetUtil.TrivialMulticlassDatasetPath, DatasetUtil.TrivialMulticlassDatasetLabel); 284var result = context.Auto() 316var result = context.Auto() 334var columnInference = context.Auto().InferColumns(datasetPath, "Label"); 346var result = context.Auto() 361var columnInference = context.Auto().InferColumns(datasetPath, "Label"); 369var result = context.Auto() 391var columnInference = context.Auto().InferColumns(datasetPath, "Label"); 398var result = context.Auto() 429var experiment = mlContext.Auto() 486var experiment = mlContext.Auto() 530ExperimentResult<RegressionMetrics> experimentResult = mlContext.Auto() 586var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel); 600var modelFull = context.Auto() 607var modelTrainTest = context.Auto() 614var modelCV = context.Auto() 650var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel); 653var experiment = context.Auto()
AutoMLExperimentTests.cs (34)
36var experiment = context.Auto().CreateExperiment(); 66var experiment = context.Auto().CreateExperiment(); 104var experiment = context.Auto().CreateExperiment(); 105var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 124var experiment = context.Auto().CreateExperiment(); 163var experiment = context.Auto().CreateExperiment(); 186var experiment = context.Auto().CreateExperiment(); 221var experiment = context.Auto().CreateExperiment(); 222var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 223.Append(context.Auto().BinaryClassification(DatasetUtil.UciAdultLabel, "_Features_", useLgbm: false, useSdcaLogisticRegression: false, useLbfgsLogisticRegression: false)); 246var experiment = context.Auto().CreateExperiment(); 247var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 248.Append(context.Auto().BinaryClassification(DatasetUtil.UciAdultLabel, "_Features_", exampleWeightColumnName: "signedWeight", useLgbm: false, useSdcaLogisticRegression: false, useLbfgsLogisticRegression: false)); 271var experiment = context.Auto().CreateExperiment(); 272var pipeline = context.Auto().Featurizer(data, "_Features_", excludeColumns: new[] { DatasetUtil.UciAdultLabel }) 273.Append(context.Auto().BinaryClassification(DatasetUtil.UciAdultLabel, "_Features_", useLgbm: false, useSdcaLogisticRegression: false, useLbfgsLogisticRegression: false)); 296var experiment = context.Auto().CreateExperiment(); 298var pipeline = context.Auto().Featurizer(data, excludeColumns: new[] { label }) 300.Append(context.Auto().MultiClassification(label, useLgbm: false, useSdcaMaximumEntrophy: false, useLbfgsMaximumEntrophy: false)); 323var experiment = context.Auto().CreateExperiment(); 325var pipeline = context.Auto().Featurizer(data, excludeColumns: new[] { label }) 327.Append(context.Auto().MultiClassification(label, useLgbm: false, useSdcaMaximumEntrophy: false, useLbfgsMaximumEntrophy: false)); 351var experiment = context.Auto().CreateExperiment(); 353var pipeline = context.Auto().Featurizer(train, excludeColumns: new[] { label }) 354.Append(context.Auto().Regression(label, useLgbm: false, useSdca: false, useLbfgsPoissonRegression: false)); 365experiment = context.Auto().CreateExperiment(); 381var experiment = context.Auto().CreateExperiment(); 383var pipeline = context.Auto().Featurizer(train, excludeColumns: new[] { label }) 384.Append(context.Auto().Regression(label, useLgbm: false, useSdca: false, useLbfgsPoissonRegression: false)); 400var experiment = context.Auto().CreateExperiment(); 402var pipeline = context.Auto().Featurizer(train, excludeColumns: new[] { label }) 403.Append(context.Auto().Regression(label, useLgbm: false, useSdca: false, useLbfgsPoissonRegression: false)); 419var experiment = context.Auto().CreateExperiment(); 424experiment = context.Auto().CreateExperiment();
ColumnInferenceTests.cs (13)
33var columnInferenceWithoutGrouping = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel, groupColumns: false); 39var columnInferenceWithGrouping = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel, groupColumns: true); 48Assert.Throws<ArgumentException>(new System.Action(() => context.Auto().InferColumns(dataPath, "Junk", groupColumns: false))); 54Assert.Throws<ArgumentOutOfRangeException>(() => new MLContext(1).Auto().InferColumns(DatasetUtil.GetUciAdultDataset(), 100)); 60var result = new MLContext(1).Auto().InferColumns(DatasetUtil.GetUciAdultDataset(), 14, hasHeader: true); 70var result = new MLContext(1).Auto().InferColumns(DatasetUtil.GetIrisDataset(), DatasetUtil.IrisDatasetLabelColIndex); 81var result = new MLContext(1).Auto().InferColumns(Path.Combine("TestData", "DatasetWithEmptyColumn.txt"), DefaultColumnNames.Label, groupColumns: false); 89var result = new MLContext(1).Auto().InferColumns(Path.Combine("TestData", "BinaryDatasetWithBoolColumn.txt"), DefaultColumnNames.Label); 136var result = new MLContext(1).Auto().InferColumns(Path.Combine("TestData", "NameColumnIsOnlyFeatureDataset.txt"), DefaultColumnNames.Label); 152var result = new MLContext(1).Auto() 173var result = new MLContext(1).Auto().InferColumns(Path.Combine("TestData", "DatasetWithDefaultColumnNames.txt"), 190var result = new MLContext(1).Auto().InferColumns(DatasetUtil.GetMlNetGeneratedRegressionDataset(), 222var result = mlContext.Auto().InferColumns(dataPath, inputColumnInformation);
DatasetUtil.cs (6)
58var columnInferenceResult = context.Auto().InferColumns(uciAdultDataFile, UciAdultLabel); 71var columnInferenceResult = context.Auto().InferColumns(dataFile, 0, groupColumns: false); 84var columnInferenceResult = context.Auto().InferColumns(taxiFareFile, TaxiFareLabel); 97var columnInferenceResult = context.Auto().InferColumns(file, NewspaperChurnLabel); 109var columnInferenceResult = context.Auto().InferColumns(file, "A16"); 120var columnInferenceResult = context.Auto().InferColumns(taxiFareFile, TaxiFareLabel);
SweepableExtensionTest.cs (8)
82.Append(context.Auto().BinaryClassification()); 95.Append(context.Auto().MultiClassification()); 108.Append(context.Auto().MultiClassification()); 121.Append(context.Auto().MultiClassification()); 135.Append(context.Auto().MultiClassification()); 149.Append(context.Auto().MultiClassification().Estimators.Select(kv => kv.Value).ToArray()); 162.Append(context.Auto().MultiClassification().Estimators.Select(kv => kv.Value).ToArray()); 175.Append(context.Auto().MultiClassification().Estimators.Select(kv => kv.Value).ToArray());
TrainValidaionDatasetManagerTest.cs (1)
30var columnInference = context.Auto().InferColumns(dataPath, DatasetUtil.UciAdultLabel);
TunerTests.cs (1)
461return mapKeyToValue.Append(context.Auto().BinaryClassification());
Utils\TaskAgnosticAutoFit.cs (3)
62var classificationResult = _context.Auto() 84var regressionResult = _context.Auto() 106var recommendationResult = _context.Auto()
Microsoft.ML.Fairlearn.Tests (2)
GridSearchTest.cs (2)
91var experiment = context.Auto().CreateExperiment(); 97.Append(context.Auto().BinaryClassification(labelColumnName: "y", exampleWeightColumnName: "signedWeight"));