1 write to TestSet
Microsoft.ML.Data (1)
DataLoadSave\DataOperationsCatalog.cs (1)
43
TestSet
= testSet;
85 references to TestSet
Microsoft.ML.AutoML (10)
API\AutoMLExperimentExtension.cs (2)
49
/// to train a model, and use <see cref="TrainTestData.
TestSet
"/> from <paramref name="trainValidationSplit"/> to evaluate the model.
56
return experiment.SetDataset(trainValidationSplit.TrainSet, trainValidationSplit.
TestSet
);
API\BinaryClassificationExperiment.cs (1)
184
_experiment.SetDataset(splitData.TrainSet, splitData.
TestSet
);
API\MulticlassClassificationExperiment.cs (1)
168
return Execute(splitData.TrainSet, splitData.
TestSet
, columnInformation, preFeaturizer, progressHandler);
API\RegressionExperiment.cs (1)
190
return Execute(splitData.TrainSet, splitData.
TestSet
, columnInformation, preFeaturizer, progressHandler);
AutoMLExperiment\Runner\SweepablePipelineRunner.cs (1)
53
var eval = model.Transform(split.
TestSet
);
Tuner\SmacTuner.cs (1)
150
var test = model.Transform(trainTestSplit.
TestSet
);
Utils\SplitUtil.cs (3)
24
DatasetDimensionsUtil.IsDataViewEmpty(split.
TestSet
))
30
var validationDataset = DropAllColumnsExcept(context, split.
TestSet
, originalColumnNames);
55
var validationData = DropAllColumnsExcept(context, splitData.
TestSet
, originalColumnNames);
Microsoft.ML.AutoML.Samples (2)
AutoMLExperiment.cs (1)
60
var eval = bestModel.Transform(trainTestSplit.
TestSet
);
Sweepable\SweepableLightGBMBinaryExperiment.cs (1)
87
var eval = bestModel.Transform(trainTestSplit.
TestSet
);
Microsoft.ML.AutoML.Tests (3)
AutoFitTests.cs (3)
114
.Execute(dataTrainTest.TrainSet, dataTrainTest.
TestSet
, DatasetUtil.UciAdultLabel);
173
.Execute(trainTestSplit.TrainSet, trainTestSplit.
TestSet
, label);
340
IDataView testDataset = SplitUtil.DropAllColumnsExcept(context, trainTestData.
TestSet
, originalColumnNames);
Microsoft.ML.Data (2)
TrainCatalog.cs (2)
109
scoredTest = (Unsafe.As<TransformerChain<ITransformer>>(model)).Transform(split.
TestSet
, TransformerScope.Everything);
111
scoredTest = model.Transform(split.
TestSet
);
Microsoft.ML.IntegrationTests (2)
Training.cs (1)
38
var testData = trainTestSplit.
TestSet
;
Validation.cs (1)
109
var validData = dataSplit.
TestSet
;
Microsoft.ML.PerformanceTests (1)
ImageClassificationBench.cs (1)
73
_testDataset = trainTestData.
TestSet
;
Microsoft.ML.Samples (25)
Dynamic\DataOperations\CrossValidationSplit.cs (6)
39
.CreateEnumerable<DataPoint>(folds[0].
TestSet
,
63
.CreateEnumerable<DataPoint>(folds[1].
TestSet
,
86
.CreateEnumerable<DataPoint>(folds[2].
TestSet
,
111
.CreateEnumerable<DataPoint>(folds[0].
TestSet
,
134
.CreateEnumerable<DataPoint>(folds[1].
TestSet
,
156
testSet = mlContext.Data.CreateEnumerable<DataPoint>(folds[2].
TestSet
,
Dynamic\DataOperations\TrainTestSplit.cs (2)
38
.CreateEnumerable<DataPoint>(split.
TestSet
, reuseRowObject: false);
62
.CreateEnumerable<DataPoint>(split.
TestSet
, reuseRowObject: false);
Dynamic\ModelOperations\OnnxConversion.cs (2)
89
var output = transformer.Transform(trainTestOriginalData.
TestSet
);
90
var onnxOutput = onnxTransformer.Transform(trainTestOriginalData.
TestSet
);
Dynamic\Trainers\BinaryClassification\Calibrators\FixedPlatt.cs (1)
38
var scoredData = transformer.Transform(trainTestData.
TestSet
);
Dynamic\Trainers\BinaryClassification\Calibrators\Isotonic.cs (1)
38
var scoredData = transformer.Transform(trainTestData.
TestSet
);
Dynamic\Trainers\BinaryClassification\Calibrators\Naive.cs (1)
38
var scoredData = transformer.Transform(trainTestData.
TestSet
);
Dynamic\Trainers\BinaryClassification\Calibrators\Platt.cs (1)
38
var scoredData = transformer.Transform(trainTestData.
TestSet
);
Dynamic\Trainers\BinaryClassification\Gam.cs (1)
29
var validSet = dataSets.
TestSet
;
Dynamic\Trainers\BinaryClassification\GamWithOptions.cs (1)
30
var validSet = dataSets.
TestSet
;
Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (1)
62
IDataView testDataset = trainTestData.
TestSet
;
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (1)
61
IDataView testDataset = trainTestData.
TestSet
;
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (1)
61
IDataView testDataset = trainTestData.
TestSet
;
Dynamic\Trainers\Regression\GamAdvanced.cs (1)
29
var validSet = dataSets.
TestSet
;
Dynamic\Trainers\Regression\GamWithOptionsAdvanced.cs (1)
30
var validSet = dataSets.
TestSet
;
Dynamic\Trainers\Regression\LightGbmAdvanced.cs (1)
61
var dataWithPredictions = model.Transform(split.
TestSet
);
Dynamic\Trainers\Regression\LightGbmWithOptionsAdvanced.cs (1)
70
var dataWithPredictions = model.Transform(split.
TestSet
);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresAdvanced.cs (1)
63
var dataWithPredictions = model.Transform(split.
TestSet
);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptionsAdvanced.cs (1)
67
var dataWithPredictions = model.Transform(split.
TestSet
);
Microsoft.ML.Samples.GPU (3)
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (1)
62
IDataView testDataset = trainTestData.
TestSet
;
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (1)
61
IDataView testDataset = trainTestData.
TestSet
;
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (1)
61
IDataView testDataset = trainTestData.
TestSet
;
Microsoft.ML.TensorFlow.Tests (5)
TensorflowTests.cs (5)
1416
IDataView testDataset = trainTestData.
TestSet
;
1491
IDataView testDataset = trainTestData.
TestSet
;
1623
IDataView testDataset = trainTestData.
TestSet
;
1778
IDataView testDataset = trainTestData.
TestSet
;
1868
IDataView testDataset = trainTestData.
TestSet
;
Microsoft.ML.Tests (29)
Scenarios\Api\CookbookSamples\CookbookSamplesDynamicApi.cs (1)
660
var metrics = mlContext.MulticlassClassification.Evaluate(model.Transform(split.
TestSet
, TransformerScope.Everything));
Scenarios\Api\TestApi.cs (26)
319
ttSplit.
TestSet
,
321
ttSplitWithSeed.
TestSet
,
323
ttSplitWithSeedAndSamplingKey.
TestSet
,
325
cvSplit.First().
TestSet
,
327
cvSplitWithSeed.First().
TestSet
,
329
cvSplitWithSeedAndSamplingKey.First().
TestSet
368
var simpleTestWorkClass = getWorkclass(simpleSplit.
TestSet
);
370
var simpleWithSeedTestWorkClass = getWorkclass(splitWithSeed.
TestSet
);
379
var stratTestWorkClass = getWorkclass(stratSplit.
TestSet
);
391
var stratTestWithSeedWorkClass = getWorkclass(stratSeed.
TestSet
);
457
var ids = split.
TestSet
.GetColumn<int>(split.
TestSet
.Schema[nameof(Input.Id)]);
461
ids = split.
TestSet
.GetColumn<int>(split.
TestSet
.Schema[nameof(Input.Id)]);
465
ids = split.
TestSet
.GetColumn<int>(split.
TestSet
.Schema[nameof(Input.Id)]);
469
ids = split.
TestSet
.GetColumn<int>(split.
TestSet
.Schema[nameof(Input.Id)]);
477
ids = split.
TestSet
.GetColumn<int>(split.
TestSet
.Schema[nameof(Input.Id)]);
483
ids = split.
TestSet
.GetColumn<int>(split.
TestSet
.Schema[nameof(Input.Id)]);
501
var idsTest1 = cvSplits[0].
TestSet
.GetColumn<int>(cvSplits[0].
TestSet
.Schema[nameof(Input.Id)]);
502
var idsTest2 = cvSplits[1].
TestSet
.GetColumn<int>(cvSplits[1].
TestSet
.Schema[nameof(Input.Id)]);
Scenarios\RegressionTest.cs (1)
42
var predictions = model.Transform(splitData.
TestSet
);
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (1)
801
var testData = split.
TestSet
;
Microsoft.ML.TorchSharp.Tests (3)
NerTests.cs (1)
235
var output = transformer.Transform(trainTest.
TestSet
);
TextClassificationTests.cs (2)
181
var predictionIdv = model.Transform(trainTestSplit.
TestSet
);
444
var transformedData = model.Transform(dataSplit.
TestSet
);