2 instantiations of TrainTestData
Microsoft.ML.Data (2)
DataLoadSave\DataOperationsCatalog.cs (2)
437return new TrainTestData(trainDV, testDV); 503yield return new TrainTestData(trainDV, testDV);
66 references to TrainTestData
Microsoft.ML.AutoML (11)
API\AutoMLExperimentExtension.cs (4)
48/// Set train and validation dataset for <see cref="AutoMLExperiment"/>. This will make <see cref="AutoMLExperiment"/> uses <see cref="TrainTestData.TrainSet"/> from <paramref name="trainValidationSplit"/> 49/// to train a model, and use <see cref="TrainTestData.TestSet"/> from <paramref name="trainValidationSplit"/> to evaluate the model. 52/// <param name="trainValidationSplit">a <see cref="TrainTestData"/> for train and validation.</param> 54public static AutoMLExperiment SetDataset(this AutoMLExperiment experiment, TrainTestData trainValidationSplit)
API\BinaryClassificationExperiment.cs (1)
183var splitData = Context.Data.TrainTestSplit(trainData);
API\MulticlassClassificationExperiment.cs (1)
167var splitData = Context.Data.TrainTestSplit(trainData);
API\RegressionExperiment.cs (1)
189var splitData = Context.Data.TrainTestSplit(trainData);
AutoMLExperiment\Runner\SweepablePipelineRunner.cs (1)
46foreach (var split in datasetSplit)
Tuner\SmacTuner.cs (1)
147var trainTestSplit = _context.Data.TrainTestSplit(data);
Utils\SplitUtil.cs (2)
21foreach (var split in splits) 53var splitData = context.Data.TrainTestSplit(trainData, samplingKeyColumnName: samplingKeyColumn);
Microsoft.ML.AutoML.Samples (2)
AutoMLExperiment.cs (1)
26var trainTestSplit = context.Data.TrainTestSplit(dataView);
Sweepable\SweepableLightGBMBinaryExperiment.cs (1)
39var trainTestSplit = context.Data.TrainTestSplit(dataView, testFraction: 0.1);
Microsoft.ML.AutoML.Tests (4)
AutoFitTests.cs (4)
102var dataTrainTest = context.Data.TrainTestSplit(trainData); 161var trainTestSplit = context.Data.TrainTestSplit(dataset); 338TrainTestData trainTestData = context.Data.TrainTestSplit(trainData, testFraction: 0.2, seed: 1); 589var dataTrainTest = context.Data.TrainTestSplit(dataFull);
Microsoft.ML.Data (6)
DataLoadSave\DataOperationsCatalog.cs (5)
411public TrainTestData TrainTestSplit(IDataView data, double testFraction = 0.1, string samplingKeyColumnName = null, int? seed = null) 458public IReadOnlyList<TrainTestData> CrossValidationSplit(IDataView data, int numberOfFolds = 5, string samplingKeyColumnName = null, int? seed = null) 464var result = new List<TrainTestData>(); 465foreach (var split in CrossValidationSplit(_env, data, splitColumn, numberOfFolds)) 474internal static IEnumerable<TrainTestData> CrossValidationSplit(IHostEnvironment env, IDataView data, string splitColumn, int numberOfFolds = 5)
TrainCatalog.cs (1)
103foreach (var split in DataOperationsCatalog.CrossValidationSplit(Environment, data, splitColumn, numFolds))
Microsoft.ML.Fairlearn.Tests (1)
GridSearchTest.cs (1)
94var trainTestSplit = context.Data.TrainTestSplit(shuffledDataset, 0.2);
Microsoft.ML.IntegrationTests (2)
Training.cs (1)
36var trainTestSplit = mlContext.Data.TrainTestSplit(data);
Validation.cs (1)
107var dataSplit = mlContext.Data.TrainTestSplit(data, testFraction: 0.2);
Microsoft.ML.PerformanceTests (1)
ImageClassificationBench.cs (1)
69TrainTestData trainTestData = _mlContext.Data.TrainTestSplit(
Microsoft.ML.Samples (17)
Dynamic\DataOperations\TrainTestSplit.cs (1)
30var split = mlContext.Data
Dynamic\ModelOperations\OnnxConversion.cs (1)
45var trainTestOriginalData = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\FixedPlatt.cs (1)
23var trainTestData = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\Isotonic.cs (1)
23var trainTestData = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\Naive.cs (1)
23var trainTestData = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\Platt.cs (1)
23var trainTestData = mlContext.Data
Dynamic\Trainers\BinaryClassification\Gam.cs (1)
27var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\BinaryClassification\GamWithOptions.cs (1)
28var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (1)
58TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (1)
57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (1)
57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Dynamic\Trainers\Regression\GamAdvanced.cs (1)
27var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\Regression\GamWithOptionsAdvanced.cs (1)
28var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\Regression\LightGbmAdvanced.cs (1)
30var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.1);
Dynamic\Trainers\Regression\LightGbmWithOptionsAdvanced.cs (1)
30var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.1);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresAdvanced.cs (1)
49var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.2);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptionsAdvanced.cs (1)
49var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.2);
Microsoft.ML.Samples.GPU (3)
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (1)
58TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (1)
57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (1)
57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Microsoft.ML.TensorFlow.Tests (5)
TensorflowTests.cs (5)
1412TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1487TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1619TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1774TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1864TrainTestData trainTestData = _mlContext.Data.TrainTestSplit(
Microsoft.ML.Tests (11)
Scenarios\Api\CookbookSamples\CookbookSamplesDynamicApi.cs (1)
655var split = mlContext.Data.TrainTestSplit(data, testFraction: 0.1);
Scenarios\Api\TestApi.cs (8)
308var ttSplit = mlContext.Data.TrainTestSplit(fullInput); 309var ttSplitWithSeed = mlContext.Data.TrainTestSplit(fullInput, seed: 10); 310var ttSplitWithSeedAndSamplingKey = mlContext.Data.TrainTestSplit(fullInput, seed: 10, samplingKeyColumnName: "Workclass"); 364var simpleSplit = mlContext.Data.TrainTestSplit(input); 365var splitWithSeed = mlContext.Data.TrainTestSplit(input, seed: 10); 377var stratSplit = mlContext.Data.TrainTestSplit(input, samplingKeyColumnName: "Workclass"); 389var stratSeed = mlContext.Data.TrainTestSplit(input, samplingKeyColumnName: "Workclass", seed: 1000000); 456var split = mlContext.Data.TrainTestSplit(input, 0.5, nameof(Input.TextStrat));
Scenarios\RegressionTest.cs (1)
23var splitData = context.Data.TrainTestSplit(taxiData, testFraction: 0.1);
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (1)
799var split = ML.Data.TrainTestSplit(dataView, 0.5);
Microsoft.ML.TorchSharp.Tests (3)
NerTests.cs (1)
217var trainTest = ML.Data.TrainTestSplit(dataView);
TextClassificationTests.cs (2)
175var trainTestSplit = mlContext.Data.TrainTestSplit(df, testFraction: 0.2); 432var dataSplit = ML.Data.TrainTestSplit(dataView, testFraction: 0.2);