1 write to Data
Microsoft.ML.Data (1)
MLContext.cs (1)
159Data = new DataOperationsCatalog(_env);
1473 references to Data
Microsoft.Data.Analysis.Tests (2)
DataFrameIDataViewTests.cs (2)
365IDataView data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 488var data = mlContext.Data.LoadFromEnumerable(inputData);
Microsoft.ML.AutoML (16)
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\IDatasetManager.cs (1)
89var subSampledTrainDataset = context.Data.TakeRows(_trainDataset, count);
AutoMLExperiment\ITrialResultManager.cs (1)
148var dataView = context.Data.LoadFromTextFile(filePath, textLoaderColumns, separatorChar: ',', hasHeader: true, allowQuoting: true);
AutoMLExperiment\Runner\SweepablePipelineRunner.cs (1)
43var datasetSplit = _mLContext!.Data.CrossValidationSplit(crossValidateDatasetManager.Dataset, crossValidateDatasetManager.Fold, crossValidateDatasetManager.SamplingKeyColumnName);
ColumnInference\ColumnInferenceApi.cs (1)
62var textLoader = context.Data.CreateTextLoader(typedLoaderOptions);
ColumnInference\ColumnTypeInference.cs (2)
268var textLoader = context.Data.CreateTextLoader(textLoaderOptions); 270idv = context.Data.TakeRows(idv, args.MaxRowsToRead);
ColumnInference\PurposeInference.cs (1)
244data = context.Data.TakeRows(data, MaxRowsToRead);
ColumnInference\TextFileContents.cs (2)
93var textLoader = context.Data.CreateTextLoader(options, source); 94var idv = context.Data.TakeRows(textLoader.Load(source), 1000);
DatasetDimensions\DatasetDimensionsApi.cs (1)
15data = context.Data.TakeRows(data, MaxRowsToRead);
Tuner\SmacTuner.cs (1)
147var trainTestSplit = _context.Data.TrainTestSplit(data);
Utils\SplitUtil.cs (2)
17var splits = context.Data.CrossValidationSplit(trainData, (int)numFolds, samplingKeyColumnName: samplingKeyColumn); 53var splitData = context.Data.TrainTestSplit(trainData, samplingKeyColumnName: samplingKeyColumn);
Microsoft.ML.AutoML.Samples (16)
AutoFit\BinaryClassificationExperiment.cs (2)
21IDataView trainDataView = mlContext.Data.LoadFromTextFile<SentimentIssue>(TrainDataPath, hasHeader: true); 22IDataView testDataView = mlContext.Data.LoadFromTextFile<SentimentIssue>(TestDataPath, hasHeader: true);
AutoFit\MulticlassClassificationExperiment.cs (2)
22IDataView trainDataView = mlContext.Data.LoadFromTextFile<PixelData>(TrainDataPath, separatorChar: ','); 23IDataView testDataView = mlContext.Data.LoadFromTextFile<PixelData>(TestDataPath, separatorChar: ',');
AutoFit\RankingExperiment.cs (2)
25IDataView trainDataView = mlContext.Data.LoadFromTextFile<SearchData>(TrainDataPath, hasHeader: true, separatorChar: ','); 26IDataView testDataView = mlContext.Data.LoadFromTextFile<SearchData>(TestDataPath, hasHeader: true, separatorChar: ',');
AutoFit\RecommendationExperiment.cs (2)
28IDataView trainDataView = mlContext.Data.LoadFromTextFile<Movie>(TrainDataPath, hasHeader: true, separatorChar: ','); 29IDataView testDataView = mlContext.Data.LoadFromTextFile<Movie>(TestDataPath, hasHeader: true, separatorChar: ',');
AutoFit\RegressionExperiment.cs (2)
22IDataView trainDataView = mlContext.Data.LoadFromTextFile<TaxiTrip>(TrainDataPath, hasHeader: true, separatorChar: ','); 23IDataView testDataView = mlContext.Data.LoadFromTextFile<TaxiTrip>(TestDataPath, hasHeader: true, separatorChar: ',');
AutoMLExperiment.cs (2)
24var dataView = context.Data.LoadFromEnumerable(data); 26var trainTestSplit = context.Data.TrainTestSplit(dataView);
Cifar10.cs (2)
35var trainDataset = context.Data.LoadFromEnumerable(trainImages); 36var testDataset = context.Data.LoadFromEnumerable(testImages);
Sweepable\SweepableLightGBMBinaryExperiment.cs (2)
36var dataView = context.Data.LoadFromEnumerable(data); 39var trainTestSplit = context.Data.TrainTestSplit(dataView, testFraction: 0.1);
Microsoft.ML.AutoML.Tests (35)
AutoFeaturizerTests.cs (1)
109var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions);
AutoFitTests.cs (23)
47var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 73var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 100var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 102var dataTrainTest = context.Data.TrainTestSplit(trainData); 127var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 161var trainTestSplit = context.Data.TrainTestSplit(dataset); 243.Execute(context.Data.TakeRows(dataset, 1000), label); 250var model = result.BestRun.Estimator.Fit(context.Data.TakeRows(dataset, 1000)); 261var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 306trainData = context.Data.TakeRows(trainData, crossValRowCountThreshold - 1); 335var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 336var trainData = context.Data.ShuffleRows(textLoader.Load(datasetPath), seed: 1); 338TrainTestData trainTestData = context.Data.TrainTestSplit(trainData, testFraction: 0.2, seed: 1); 362var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 363var trainData = context.Data.ShuffleRows(textLoader.Load(datasetPath), seed: 1); 392var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 420var testDataView = mlContext.Data.TakeRows(trainDataView, 500); 421trainDataView = mlContext.Data.SkipRows(trainDataView, 500); 484trainDataView = mlContext.Data.TakeRows(trainDataView, 1499); 587var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions); 589var dataTrainTest = context.Data.TrainTestSplit(dataFull); 590var dataCV = context.Data.CrossValidationSplit(dataFull, numberOfFolds: 2); 651var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions);
AutoMLExperimentTests.cs (4)
108experiment.SetDataset(context.Data.TrainTestSplit(data)) 225experiment.SetDataset(context.Data.TrainTestSplit(data)) 250experiment.SetDataset(context.Data.TrainTestSplit(data)) 329experiment.SetDataset(context.Data.TrainTestSplit(data))
DatasetUtil.cs (6)
59var textLoader = context.Data.CreateTextLoader(columnInferenceResult.TextLoaderOptions); 72var textLoader = context.Data.CreateTextLoader(columnInferenceResult.TextLoaderOptions); 85var textLoader = context.Data.CreateTextLoader(columnInferenceResult.TextLoaderOptions); 98var textLoader = context.Data.CreateTextLoader(columnInferenceResult.TextLoaderOptions); 110var textLoader = context.Data.CreateTextLoader(columnInferenceResult.TextLoaderOptions); 121var textLoader = context.Data.CreateTextLoader(columnInferenceResult.TextLoaderOptions);
TrainValidaionDatasetManagerTest.cs (1)
31var textLoader = context.Data.CreateTextLoader(columnInference.TextLoaderOptions);
Microsoft.ML.CodeGenerator (1)
Utils.cs (1)
42var textLoader = mlContext.Data.CreateTextLoader(columnInference.TextLoaderOptions);
Microsoft.ML.CodeGenerator.Tests (2)
UtilTest.cs (2)
131var dataView = context.Data.LoadFromTextFile<TestClass>(filePath, separatorChar: ',', hasHeader: true); 166var dataView = context.Data.LoadFromTextFile<TestClassContainsDuplicates>(filePath, separatorChar: ',', hasHeader: true);
Microsoft.ML.Core.Tests (12)
UnitTests\TestCustomTypeRegister.cs (2)
184var tribeDataView = ML.Data.LoadFromEnumerable(tribe); 188var tribeEnumerable = ML.Data.CreateEnumerable<SuperAlienHero>(tribeTransformed, false).ToList();
UnitTests\TestEntryPoints.cs (9)
745var loadedData = mlContext.Data.LoadFromBinary(outputDataPath); 893var loadedData = mlContext.Data.LoadFromBinary(outputDataPath); 1054var loadedData = mlContext.Data.LoadFromBinary(outputDataPath); 1197var loadedData = mlContext.Data.LoadFromBinary(outputDataPath); 1344var loadedData = mlContext.Data.LoadFromBinary(outputDataPath); 1440var loadedData = mlContext.Data.LoadFromBinary(outputDataPath); 4719var data = ML.Data.LoadFromTextFile(dataPath, new[] 4761var data = ML.Data.LoadFromTextFile(dataPath, new[] 6664ML.Data.SaveAsText(data, f);
UnitTests\TestHosts.cs (1)
131env.Data.CreateTextLoader(new TextLoader.Options { Columns = new[] { new TextLoader.Column("TestColumn", DataKind.Single, 0) } });
Microsoft.ML.Fairlearn (1)
Metrics\FairlearnMetricCatalog.cs (1)
94.ToDictionary(group => group.Key, group => _context.Data.LoadFromEnumerable(group.Select(g => g.Item2)));
Microsoft.ML.Fairlearn.Tests (3)
GridSearchTest.cs (2)
93var shuffledDataset = context.Data.ShuffleRows(df); 94var trainTestSplit = context.Data.TrainTestSplit(shuffledDataset, 0.2);
MetricTest.cs (1)
19data = mlContext.Data.LoadFromEnumerable(houseData);
Microsoft.ML.IntegrationTests (116)
Common.cs (2)
75var enumerable1 = mlContext.Data.CreateEnumerable<TypeTestData>(data1, true); 76var enumerable2 = mlContext.Data.CreateEnumerable<TypeTestData>(data2, true);
DataIO.cs (10)
36var data = mlContext.Data.LoadFromEnumerable(TypeTestData.GenerateDataset()); 51var data = mlContext.Data.LoadFromEnumerable(enumerableBefore); 54var enumerableAfter = mlContext.Data.CreateEnumerable<TypeTestData>(data, true); 70var dataBefore = mlContext.Data.LoadFromEnumerable(TypeTestData.GenerateDataset()); 92var dataBefore = mlContext.Data.LoadFromEnumerable(TypeTestData.GenerateDataset()); 98var dataAfter = mlContext.Data.LoadFromTextFile<TypeTestData>(filePath, separatorChar: separator, hasHeader: true, allowQuoting: true); 111var dataBefore = mlContext.Data.LoadFromEnumerable(TypeTestData.GenerateDataset()); 115var dataAfter = mlContext.Data.LoadFromBinary(filePath); 123mlContext.Data.SaveAsText(data, file, separatorChar: separator, headerRow: true); 132mlContext.Data.SaveAsBinary(data, file);
Datasets\Iris.cs (1)
39var data = mlContext.Data.LoadFromTextFile<Iris>(filePath, hasHeader: hasHeader, separatorChar: separatorChar);
Datasets\MnistOneClass.cs (1)
19return mlContext.Data.CreateTextLoader(
Datasets\TrivialMatrixFactorization.cs (1)
27var data = mlContext.Data.LoadFromTextFile<TrivialMatrixFactorization>(filePath, hasHeader: hasHeader, separatorChar: separatorChar);
Datasets\TypeTestData.cs (1)
79return mlContext.Data.CreateTextLoader(
DataTransformation.cs (11)
32var data = mlContext.Data.LoadFromTextFile<Iris>( 39data = mlContext.Data.TakeRows(data, numSamples); 67var transformedRows = mlContext.Data.CreateEnumerable<IrisWithOneExtraColumn>(transformedData, reuseRowObject: true); 85var data = mlContext.Data.LoadFromTextFile<Iris>( 92data = mlContext.Data.TakeRows(data, numSamples); 113var transformedRows = mlContext.Data.CreateEnumerable<IrisWithTwoExtraColumns>(transformedData, reuseRowObject: true); 132var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 169var data = mlContext.Data.LoadFromTextFile<Iris>( 182var dataEnumerator = mlContext.Data.CreateEnumerable<FeatureColumn>(transformedData, true); 196var data = mlContext.Data.LoadFromTextFile<Iris>( 210var dataEnumerator = mlContext.Data.CreateEnumerable<HashedFeatureColumn>(transformedData, true);
Debugging.cs (6)
40var data = mlContext.Data.LoadFromEnumerable<TweetSentiment>( 104var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 133var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 147foreach (var row in mlContext.Data.CreateEnumerable<HousingRegression>(mlContext.Data.TakeRows(data, 1), true)) 171var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true);
Evaluation.cs (6)
60var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 89var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 118var data = mlContext.Data.LoadFromTextFile<Iris>(TestCommon.GetDataPath(DataDir, TestDatasets.iris.trainFilename), 146var data = mlContext.Data.LoadFromTextFile<Iris>(TestCommon.GetDataPath(DataDir, TestDatasets.iris.trainFilename), 268var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 295var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename),
Explainability.cs (20)
35var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 93var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 117var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 144var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 171var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 189var shuffledSubset = mlContext.Data.TakeRows(mlContext.Data.ShuffleRows(outputData), 10); 190var scoringEnumerator = mlContext.Data.CreateEnumerable<FeatureContributionOutput>(shuffledSubset, true); 208var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 226var shuffledSubset = mlContext.Data.TakeRows(mlContext.Data.ShuffleRows(outputData), 10); 227var scoringEnumerator = mlContext.Data.CreateEnumerable<FeatureContributionOutput>(shuffledSubset, true); 245var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 263var shuffledSubset = mlContext.Data.TakeRows(mlContext.Data.ShuffleRows(outputData), 10); 264var scoringEnumerator = mlContext.Data.CreateEnumerable<FeatureContributionOutput>(shuffledSubset, true); 283var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 301var shuffledSubset = mlContext.Data.TakeRows(mlContext.Data.ShuffleRows(outputData), 10); 302var scoringEnumerator = mlContext.Data.CreateEnumerable<FeatureContributionOutput>(shuffledSubset, true);
IntrospectiveTraining.cs (10)
35var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 75var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 137var data = mlContext.Data.LoadFromTextFile<Iris>( 178var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 219var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 258var data = mlContext.Data.LoadFromTextFile<Iris>( 289var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 332var data = mlContext.Data.LoadFromTextFile<Adult>(TestCommon.GetDataPath(DataDir, TestDatasets.adult.trainFilename), 369var transformedRows = mlContext.Data.CreateEnumerable<Adult>(data, false); 389var data = mlContext.Data.LoadFromTextFile<Iris>(TestCommon.GetDataPath(DataDir, TestDatasets.iris.trainFilename),
ModelFiles.cs (14)
45var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 92var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 119var dataEnumerator = mlContext.Data.CreateEnumerable<HousingRegression>(mlContext.Data.TakeRows(data, 5), false); 135var loader = mlContext.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file); 268var loader = mlContext.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file); 297data = mlContext.Data.LoadFromEnumerable(new[] { new InputData() }); 325var loader = mlContext.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file); 344data = mlContext.Data.LoadFromEnumerable(new[] { new InputData() }); 348data = mlContext.Data.LoadFromEnumerable(new[] { new InputData() }, loadedSchema); 358var loader = mlContext.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file); 387var loader = mlContext.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file); 425var loader = mlContext.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file); 458var loader = mlContext.Data.CreateTextLoader<InputData>(hasHeader: true, dataSample: file);
ONNX.cs (9)
37var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 68var dataEnumerator = mlContext.Data.CreateEnumerable<HousingRegression>(mlContext.Data.TakeRows(data, 5), false); 87var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 120var dataEnumerator = mlContext.Data.CreateEnumerable<HousingRegression>(mlContext.Data.TakeRows(data, 5), false); 139var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 167var dataEnumerator = mlContext.Data.CreateEnumerable<HousingRegression>(mlContext.Data.TakeRows(data, 5), false);
Prediction.cs (3)
46var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 82var data = mlContext.Data.LoadFromEnumerable(TypeTestData.GenerateDataset()); 105var data = mlContext.Data.LoadFromEnumerable(TypeTestData.GenerateDataset());
SchemaDefinitionTests.cs (2)
34var loader = _ml.Data.CreateTextLoader(new TextLoader.Options(), new MultiFileSource(fileName)); 65var loader = _ml.Data.CreateTextLoader(new TextLoader.Options(), new MultiFileSource(fileName));
Training.cs (12)
32var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 36var trainTestSplit = mlContext.Data.TrainTestSplit(data); 86var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 130var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 174var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 218var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 261var data = mlContext.Data.LoadFromTextFile<Iris>(TestCommon.GetDataPath(DataDir, TestDatasets.iris.trainFilename), 312var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), 356var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), 400var data = mlContext.Data.LoadFromTextFile<TweetSentiment>(TestCommon.GetDataPath(DataDir, TestDatasets.Sentiment.trainFilename), 448var data = mlContext.Data.LoadFromTextFile<Iris>(TestCommon.GetDataPath(DataDir, TestDatasets.iris.trainFilename), 479var data = mlContext.Data.LoadFromTextFile<Iris>(TestCommon.GetDataPath(DataDir, TestDatasets.iris.trainFilename),
Validation.cs (7)
38var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 73var reader = mlContext.Data.CreateTextLoader(new TextLoader.Options() 104var data = mlContext.Data.LoadFromTextFile<HousingRegression>(TestCommon.GetDataPath(DataDir, TestDatasets.housing.trainFilename), hasHeader: true); 107var dataSplit = mlContext.Data.TrainTestSplit(data, testFraction: 0.2); 153var data = mlContext.Data.LoadFromTextFile<Iris>(TestCommon.GetDataPath(DataDir, TestDatasets.iris.trainFilename), hasHeader: true); 160var scoredDataOneRow = model.Transform(mlContext.Data.TakeRows(data, 1)); 166var scoredDataZeroRows = mlContext.Data.FilterRowsByColumn(scoredDataOneRow, "Label", lowerBound: -2, upperBound: -1);
Microsoft.ML.OnnxTransformerTest (36)
DnnImageFeaturizerTest.cs (7)
80var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 81var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData); 82var invalidDataWrongVectorSize = ML.Data.LoadFromEnumerable(sizeData); 104var data = ML.Data.LoadFromTextFile(dataFile, new[] { 143var dataView = ML.Data.LoadFromEnumerable( 214var data = ML.Data.LoadFromTextFile<ModelInput>( 241ModelInput sample = ML.Data.CreateEnumerable<ModelInput>(data, false).First();
OnnxTransformTests.cs (29)
131var dataView = ML.Data.LoadFromEnumerable( 160var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 161var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData); 162var invalidDataWrongVectorSize = ML.Data.LoadFromEnumerable(sizeData); 186var dataView = ML.Data.LoadFromEnumerable( 249var data = ML.Data.LoadFromTextFile(dataFile, new[] { 300var data = ML.Data.LoadFromTextFile(dataFile, new[] { 361var dataView = ML.Data.LoadFromEnumerable( 394var dataView = ML.Data.LoadFromEnumerable( 428var dataView = ML.Data.LoadFromEnumerable( 467var dataView = ML.Data.LoadFromEnumerable( 535var idv = mlContext.Data.LoadFromEnumerable(data); 539var predictions = mlContext.Data.CreateEnumerable<PredictionUnknownDimensions>(transformedValues, reuseRowObject: false).ToArray(); 561var idv = mlContext.Data.LoadFromEnumerable(data); 565var predictions = mlContext.Data.CreateEnumerable<PredictionNoneDimension>(transformedValues, reuseRowObject: false).ToArray(); 637var dataView = ML.Data.LoadFromEnumerable(dataPoints); 651var transformedDataPoints = ML.Data.CreateEnumerable<ImageDataPoint>(onnx, false).ToList(); 693var dataView = ML.Data.LoadFromEnumerable(dataPoints); 719var transformedDataPoints = ML.Data.CreateEnumerable<ZipMapInt64Output>(transformedDataView, false).ToList(); 746var dataView = ML.Data.LoadFromEnumerable(dataPoints); 772var transformedDataPoints = ML.Data.CreateEnumerable<ZipMapStringOutput>(transformedDataView, false).ToList(); 860var dataView = ML.Data.LoadFromEnumerable(dataPoints); 864var transformedDataPoints = ML.Data.CreateEnumerable<OnnxMapOutput>(transformedDataView, false).ToList(); 900var dataView = ML.Data.LoadFromEnumerable(dataPoints); 930var transformedDataPoints = ML.Data.CreateEnumerable<PredictionWithCustomShape>(transformedDataView, false).ToList(); 962var dataView = ML.Data.LoadFromEnumerable( 1070var dataView = ML.Data.LoadFromEnumerable(dataPoints); 1094var transformedDataPoints = ML.Data.CreateEnumerable<PredictionWithCustomShape>(transformedDataView, false).ToList(); 1129var data = ML.Data.LoadFromTextFile(dataFile, new[] {
Microsoft.ML.PerformanceTests (15)
CacheDataViewBench.cs (1)
37var cacheDv = ctx.Data.Cache(dv);
FeaturizeTextBench.cs (1)
39var textLoader = _mlContext.Data.CreateTextLoader(new TextLoader.Options()
ImageClassificationBench.cs (3)
57IDataView shuffledFullImagesDataset = _mlContext.Data.ShuffleRows( 58_mlContext.Data.LoadFromEnumerable(images)); 69TrainTestData trainTestData = _mlContext.Data.TrainTestSplit(
KMeansAndLogisticRegressionBench.cs (1)
24var input = ml.Data.LoadFromTextFile(_dataPath, new[] {
RffTransform.cs (1)
32var loader = mlContext.Data.CreateTextLoader(new TextLoader.Options
ShuffleRowsBench.cs (2)
32IDataView data = _context.Data.LoadFromEnumerable(_rows); 34IDataView shuffledData = _context.Data.ShuffleRows(data, seed: 0);
StochasticDualCoordinateAscentClassifierBench.cs (4)
101var loader = _mlContext.Data.LoadFromTextFile(_sentimentDataPath, arguments); 166public void PredictIrisBatchOf1() => _trainedModel.Transform(_mlContext.Data.LoadFromEnumerable(_batches[0])); 169public void PredictIrisBatchOf2() => _trainedModel.Transform(_mlContext.Data.LoadFromEnumerable(_batches[1])); 172public void PredictIrisBatchOf5() => _trainedModel.Transform(_mlContext.Data.LoadFromEnumerable(_batches[2]));
TextLoaderBench.cs (1)
42var textLoader = _mlContext.Data.CreateTextLoader(new TextLoader.Options()
TextPredictionEngineCreation.cs (1)
24var data = _context.Data.LoadFromTextFile<SentimentData>(
Microsoft.ML.Predictor.Tests (6)
TestIniModels.cs (2)
519var idv = mlContext.Data.CreateTextLoader( 558var idv = mlContext.Data.CreateTextLoader(
TestPredictors.cs (4)
627var dataView = ML.Data.LoadFromTextFile(dataPath); 648var dataView = ML.Data.LoadFromTextFile(dataPath); 757var dataView = ML.Data.LoadFromTextFile(dataPath); 803var dataView = ML.Data.LoadFromTextFile(dataPath);
Microsoft.ML.Samples (501)
Dynamic\DataOperations\BootstrapSample.cs (3)
25var data = mlContext.Data.LoadFromEnumerable(rawData); 43var resample = mlContext.Data.BootstrapSample(data, seed: i); 45var enumerable = mlContext.Data
Dynamic\DataOperations\Cache.cs (2)
29var cachedData = mlContext.Data.Cache(data); 64var enumerable = mlContext.Data
Dynamic\DataOperations\CrossValidationSplit.cs (15)
22var dataview = mlContext.Data.LoadFromEnumerable(examples); 30var folds = mlContext.Data 34var trainSet = mlContext.Data 38var testSet = mlContext.Data 58trainSet = mlContext.Data 62testSet = mlContext.Data 81trainSet = mlContext.Data 85testSet = mlContext.Data 105folds = mlContext.Data.CrossValidationSplit(dataview, numberOfFolds: 3); 106trainSet = mlContext.Data 110testSet = mlContext.Data 129trainSet = mlContext.Data 133testSet = mlContext.Data 152trainSet = mlContext.Data 156testSet = mlContext.Data.CreateEnumerable<DataPoint>(folds[2].TestSet,
Dynamic\DataOperations\DataViewEnumerable.cs (3)
23IDataView data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 27var rowEnumerable = mlContext.Data 36var rowEnumerableIgnoreMissing = mlContext.Data
Dynamic\DataOperations\FilterRowsByColumn.cs (3)
20var data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 46var filteredData = mlContext.Data 52var enumerable = mlContext.Data
Dynamic\DataOperations\FilterRowsByCustomPredicate.cs (3)
27var data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 48var filteredData = mlContext.Data.FilterByCustomPredicate<InputData>( 52var enumerable = mlContext.Data
Dynamic\DataOperations\FilterRowsByKeyColumnFraction.cs (6)
33var data = mlContext.Data.LoadFromEnumerable(samples); 40var enumerable = mlContext.Data 68var filteredHalfData = mlContext.Data 72var filteredHalfEnumerable = mlContext.Data 95var filteredMiddleData = mlContext.Data 101var filteredMiddleEnumerable = mlContext.Data
Dynamic\DataOperations\FilterRowsByMissingValues.cs (3)
32var data = mlContext.Data.LoadFromEnumerable(samples); 35var filteredData = mlContext.Data 40var enumerable = mlContext.Data
Dynamic\DataOperations\FilterRowsByStatefulCustomPredicate.cs (3)
27var data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 48var filteredData = mlContext.Data.FilterByStatefulCustomPredicate<InputData, State>( 58var enumerable = mlContext.Data
Dynamic\DataOperations\LoadFromEnumerable.cs (2)
39IDataView data = mlContext.Data.LoadFromEnumerable(enumerableKnownSize); 81IDataView data2 = mlContext.Data
Dynamic\DataOperations\LoadingSvmLight.cs (2)
46var loader = mlContext.Data.CreateSvmLightLoader(dataSample: file); 75loader = mlContext.Data.CreateSvmLightLoader(inputSize: 10);
Dynamic\DataOperations\LoadingText.cs (6)
43var loader = mlContext.Data.CreateTextLoader( 78mlContext.Data.CreateTextLoader<Data>(hasHeader: false); 91var loaderWithUnknownLength = mlContext.Data.CreateTextLoader( 122mlContext.Data.SaveAsText(singleFileData, stream); 138var sparseLoader = mlContext.Data.CreateTextLoader( 174mlContext.Data.CreateTextLoader(options, dataSample: dataSampleWithSchema);
Dynamic\DataOperations\SaveAndLoadFromBinary.cs (4)
30IDataView data = mlContext.Data.LoadFromEnumerable(dataPoints); 35mlContext.Data.SaveAsBinary(data, stream); 38IDataView loadedData = mlContext.Data.LoadFromBinary("data.idv"); 41var loadedDataEnumerable = mlContext.Data
Dynamic\DataOperations\SaveAndLoadFromText.cs (4)
30IDataView data = mlContext.Data.LoadFromEnumerable(dataPoints); 35mlContext.Data.SaveAsText(data, stream); 38IDataView loadedData = mlContext.Data.LoadFromTextFile("data.tsv"); 41var loadedDataEnumerable = mlContext.Data
Dynamic\DataOperations\ShuffleRows.cs (3)
20var data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 39var shuffledData = mlContext.Data.ShuffleRows(data, seed: 123); 43var enumerable = mlContext.Data
Dynamic\DataOperations\SkipRows.cs (3)
19var data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 43var filteredData = mlContext.Data.SkipRows(data, 5); 47var enumerable = mlContext.Data
Dynamic\DataOperations\TakeRows.cs (3)
20var data = mlContext.Data.LoadFromEnumerable(enumerableOfData); 44var filteredData = mlContext.Data.TakeRows(data, 5); 48var enumerable = mlContext.Data
Dynamic\DataOperations\TrainTestSplit.cs (7)
22var dataview = mlContext.Data.LoadFromEnumerable(examples); 30var split = mlContext.Data 34var trainSet = mlContext.Data 37var testSet = mlContext.Data 57split = mlContext.Data.TrainTestSplit(dataview, testFraction: 0.2); 58trainSet = mlContext.Data 61testSet = mlContext.Data
Dynamic\ModelOperations\OnnxConversion.cs (3)
45var trainTestOriginalData = mlContext.Data 93var outScores = mlContext.Data.CreateEnumerable<ScoreValue>(output, reuseRowObject: false); 94var onnxOutScores = mlContext.Data.CreateEnumerable<OnnxScoreValue>(onnxOutput, reuseRowObject: false);
Dynamic\ModelOperations\SaveLoadModel.cs (1)
23var dataView = mlContext.Data.LoadFromEnumerable(data);
Dynamic\ModelOperations\SaveLoadModelFile.cs (1)
23var dataView = mlContext.Data.LoadFromEnumerable(data);
Dynamic\NgramExtraction.cs (1)
29var trainData = ml.Data.LoadFromEnumerable(data);
Dynamic\TensorFlow\ImageClassification.cs (2)
39var idv = mlContext.Data.LoadFromEnumerable(data); 52var outScores = mlContext.Data.CreateEnumerable<OutputScores>(
Dynamic\TensorFlow\TextClassification.cs (2)
42var dataView = mlContext.Data.LoadFromEnumerable(data); 45var lookupMap = mlContext.Data.LoadFromTextFile(Path.Combine(
Dynamic\TextTransform.cs (1)
31var trainData = ml.Data.LoadFromEnumerable(data);
Dynamic\Trainers\AnomalyDetection\RandomizedPcaSample.cs (2)
32var data = mlContext.Data.LoadFromEnumerable(samples); 47var results = mlContext.Data.CreateEnumerable<Result>(transformed,
Dynamic\Trainers\AnomalyDetection\RandomizedPcaSampleWithOptions.cs (2)
34var data = mlContext.Data.LoadFromEnumerable(samples); 55var results = mlContext.Data.CreateEnumerable<Result>(transformed,
Dynamic\Trainers\BinaryClassification\AveragedPerceptron.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data 42var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\AveragedPerceptronWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 46var testData = mlContext.Data 53var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\FixedPlatt.cs (3)
23var trainTestData = mlContext.Data 39var outScores = mlContext.Data 64var outScoresAndProbabilities = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\Isotonic.cs (3)
23var trainTestData = mlContext.Data 39var outScores = mlContext.Data 64var outScoresAndProbabilities = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\Naive.cs (3)
23var trainTestData = mlContext.Data 39var outScores = mlContext.Data 64var outScoresAndProbabilities = mlContext.Data
Dynamic\Trainers\BinaryClassification\Calibrators\Platt.cs (3)
23var trainTestData = mlContext.Data 39var outScores = mlContext.Data 64var outScoresAndProbabilities = mlContext.Data
Dynamic\Trainers\BinaryClassification\FactorizationMachine.cs (4)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 32trainingData = mlContext.Data.Cache(trainingData); 43var testData = mlContext.Data 50var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\FastForest.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 38var testData = mlContext.Data 45var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\FastForestWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 50var testData = mlContext.Data 57var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\FastTree.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 38var testData = mlContext.Data 45var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\FastTreeWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 50var testData = mlContext.Data 57var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\FieldAwareFactorizationMachine.cs (1)
27var trainingData = mlContext.Data.LoadFromEnumerable(data);
Dynamic\Trainers\BinaryClassification\FieldAwareFactorizationMachineWithOptions.cs (1)
28var trainingData = mlContext.Data.LoadFromEnumerable(data);
Dynamic\Trainers\BinaryClassification\Gam.cs (2)
24var data = mlContext.Data.LoadFromEnumerable(samples); 27var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\BinaryClassification\GamWithOptions.cs (2)
25var data = mlContext.Data.LoadFromEnumerable(samples); 28var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\BinaryClassification\LbfgsLogisticRegression.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data 42var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\LbfgsLogisticRegressionWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 44var testData = mlContext.Data 51var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\LdSvm.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data 42var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\LdSvmWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 44var testData = mlContext.Data 51var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\LightGbm.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 38var testData = mlContext.Data 45var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\LightGbmWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 49var testData = mlContext.Data 56var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\LinearSvm.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data 42var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\LinearSvmWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 44var testData = mlContext.Data 51var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\PermutationFeatureImportance.cs (1)
21var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\BinaryClassification\PermutationFeatureImportanceLoadFromDisk.cs (1)
18var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\BinaryClassification\PriorTrainer.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data 42var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SdcaLogisticRegression.cs (4)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 32trainingData = mlContext.Data.Cache(trainingData); 43var testData = mlContext.Data 50var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SdcaLogisticRegressionWithOptions.cs (4)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 33trainingData = mlContext.Data.Cache(trainingData); 55var testData = mlContext.Data 62var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SdcaNonCalibrated.cs (4)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 32trainingData = mlContext.Data.Cache(trainingData); 43var testData = mlContext.Data 50var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SdcaNonCalibratedWithOptions.cs (4)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 33trainingData = mlContext.Data.Cache(trainingData); 57var testData = mlContext.Data 64var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SgdCalibrated.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data 42var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SgdCalibratedWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 47var testData = mlContext.Data 54var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SgdNonCalibrated.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data 42var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SgdNonCalibratedWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 44var testData = mlContext.Data 51var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SymbolicSgdLogisticRegression.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 38var testData = mlContext.Data 45var predictions = mlContext.Data
Dynamic\Trainers\BinaryClassification\SymbolicSgdLogisticRegressionWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 47var testData = mlContext.Data 54var predictions = mlContext.Data
Dynamic\Trainers\Clustering\KMeans.cs (3)
24IDataView trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 35var testData = mlContext.Data.LoadFromEnumerable( 42var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Clustering\KMeansWithOptions.cs (3)
25IDataView trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 43var testData = mlContext.Data.LoadFromEnumerable( 50var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (3)
43IDataView shuffledFullImagesDataset = mlContext.Data.ShuffleRows( 44mlContext.Data.LoadFromEnumerable(images)); 58TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Dynamic\Trainers\MulticlassClassification\ImageClassification\LearningRateSchedulingCifarResnetTransferLearning.cs (2)
47IDataView trainDataset = mlContext.Data. 66IDataView testDataset = mlContext.Data.
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (3)
42IDataView shuffledFullImagesDataset = mlContext.Data.ShuffleRows( 43mlContext.Data.LoadFromEnumerable(images)); 57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (3)
42IDataView shuffledFullImagesDataset = mlContext.Data.ShuffleRows( 43mlContext.Data.LoadFromEnumerable(images)); 57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Dynamic\Trainers\MulticlassClassification\LbfgsMaximumEntropy.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 40var testData = mlContext.Data 47var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\LbfgsMaximumEntropyWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 48var testData = mlContext.Data 55var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\LightGbm.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 43var testData = mlContext.Data 50var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\LightGbmWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 53var testData = mlContext.Data 60var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\LogLossPerClass.cs (2)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 40var testData = mlContext.Data
Dynamic\Trainers\MulticlassClassification\NaiveBayes.cs (3)
30var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 46var testData = mlContext.Data 53var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\OneVersusAll.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 41var testData = mlContext.Data 48var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\PairwiseCoupling.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 41var testData = mlContext.Data 48var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportance.cs (1)
21var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportanceLoadFromDisk.cs (1)
24var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\MulticlassClassification\SdcaMaximumEntropy.cs (4)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 32trainingData = mlContext.Data.Cache(trainingData); 48var testData = mlContext.Data 55var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\SdcaMaximumEntropyWithOptions.cs (4)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 33trainingData = mlContext.Data.Cache(trainingData); 57var testData = mlContext.Data 64var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\SdcaNonCalibrated.cs (4)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 32trainingData = mlContext.Data.Cache(trainingData); 48var testData = mlContext.Data 55var predictions = mlContext.Data
Dynamic\Trainers\MulticlassClassification\SdcaNonCalibratedWithOptions.cs (4)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 33trainingData = mlContext.Data.Cache(trainingData); 57var testData = mlContext.Data 64var predictions = mlContext.Data
Dynamic\Trainers\Ranking\FastTree.cs (4)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 37var testData = mlContext.Data.LoadFromEnumerable( 44var topTransformedTestData = mlContext.Data.TakeRows( 48var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Ranking\FastTreeWithOptions.cs (4)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 51var testData = mlContext.Data.LoadFromEnumerable( 58var topTransformedTestData = mlContext.Data.TakeRows( 62var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Ranking\LightGbm.cs (4)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 37var testData = mlContext.Data.LoadFromEnumerable( 44var topTransformedTestData = mlContext.Data.TakeRows( 48var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Ranking\LightGbmWithOptions.cs (4)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 52var testData = mlContext.Data.LoadFromEnumerable( 59var topTransformedTestData = mlContext.Data.TakeRows( 63var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Ranking\PermutationFeatureImportance.cs (1)
21var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\Ranking\PermutationFeatureImportanceLoadFromDisk.cs (1)
23var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\Recommendation\MatrixFactorization.cs (2)
31var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 46var predictions = mlContext.Data
Dynamic\Trainers\Recommendation\MatrixFactorizationWithOptions.cs (2)
32var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 70var predictions = mlContext.Data
Dynamic\Trainers\Recommendation\OneClassMatrixFactorizationWithOptions.cs (3)
37var dataView = mlContext.Data.LoadFromEnumerable(data); 74var prediction = model.Transform(mlContext.Data.LoadFromEnumerable( 77var results = mlContext.Data.CreateEnumerable<MatrixElement>(prediction,
Dynamic\Trainers\Regression\FastForest.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 39var testData = mlContext.Data.LoadFromEnumerable( 46var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\FastForestWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 52var testData = mlContext.Data.LoadFromEnumerable( 59var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\FastTree.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 39var testData = mlContext.Data.LoadFromEnumerable( 46var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\FastTreeTweedie.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 39var testData = mlContext.Data.LoadFromEnumerable( 46var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\FastTreeTweedieWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 54var testData = mlContext.Data.LoadFromEnumerable( 61var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\FastTreeWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 55var testData = mlContext.Data.LoadFromEnumerable( 62var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\Gam.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 39var testData = mlContext.Data.LoadFromEnumerable( 46var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\GamAdvanced.cs (2)
24var data = mlContext.Data.LoadFromEnumerable(samples); 27var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\Regression\GamWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 50var testData = mlContext.Data.LoadFromEnumerable( 57var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\GamWithOptionsAdvanced.cs (2)
25var data = mlContext.Data.LoadFromEnumerable(samples); 28var dataSets = mlContext.Data.TrainTestSplit(data);
Dynamic\Trainers\Regression\LbfgsPoissonRegression.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 37var testData = mlContext.Data.LoadFromEnumerable( 44var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\LbfgsPoissonRegressionWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 51var testData = mlContext.Data.LoadFromEnumerable( 58var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\LightGbm.cs (3)
27var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 40var testData = mlContext.Data.LoadFromEnumerable( 47var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\LightGbmAdvanced.cs (1)
30var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.1);
Dynamic\Trainers\Regression\LightGbmWithOptions.cs (3)
28var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 59var testData = mlContext.Data.LoadFromEnumerable( 66var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\LightGbmWithOptionsAdvanced.cs (1)
30var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.1);
Dynamic\Trainers\Regression\OnlineGradientDescent.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 36var testData = mlContext.Data.LoadFromEnumerable( 43var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\OnlineGradientDescentWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 51var testData = mlContext.Data.LoadFromEnumerable( 58var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\OrdinaryLeastSquares.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 36var testData = mlContext.Data.LoadFromEnumerable( 43var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\OrdinaryLeastSquaresAdvanced.cs (2)
31var dataView = mlContext.Data.LoadFromTextFile(dataFile, 49var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.2);
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 48var testData = mlContext.Data.LoadFromEnumerable( 55var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\OrdinaryLeastSquaresWithOptionsAdvanced.cs (2)
31var dataView = mlContext.Data.LoadFromTextFile(dataFile, 49var split = mlContext.Data.TrainTestSplit(dataView, testFraction: 0.2);
Dynamic\Trainers\Regression\PermutationFeatureImportance.cs (1)
21var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\Regression\PermutationFeatureImportanceLoadFromDisk.cs (1)
23var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Trainers\Regression\Sdca.cs (3)
24var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 36var testData = mlContext.Data.LoadFromEnumerable( 43var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Trainers\Regression\SdcaWithOptions.cs (3)
25var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 52var testData = mlContext.Data.LoadFromEnumerable( 59var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Transforms\ApplyOnnxModel.cs (2)
26var data = mlContext.Data.LoadFromEnumerable(samples); 32var predictions = mlContext.Data.CreateEnumerable<Prediction>(
Dynamic\Transforms\ApplyONNXModelWithInMemoryImages.cs (2)
34var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 58var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\ApproximatedKernelMap.cs (1)
28var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\CalculateFeatureContribution.cs (2)
21var data = mlContext.Data.LoadFromEnumerable(samples); 49var simpleScoredDataset = linearModel.Transform(mlContext.Data
Dynamic\Transforms\CalculateFeatureContributionCalibrated.cs (2)
21var data = mlContext.Data.LoadFromEnumerable(samples); 51var simpleScoredDataset = linearModel.Transform(mlContext.Data
Dynamic\Transforms\Categorical\OneHotEncoding.cs (1)
27IDataView data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Categorical\OneHotEncodingMultiColumn.cs (2)
25IDataView data = mlContext.Data.LoadFromEnumerable(samples); 42mlContext.Data.CreateEnumerable<TransformedData>(transformedData,
Dynamic\Transforms\Categorical\OneHotHashEncoding.cs (1)
27IDataView data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Categorical\OneHotHashEncodingMultiColumn.cs (2)
25IDataView data = mlContext.Data.LoadFromEnumerable(samples); 43mlContext.Data.CreateEnumerable<TransformedData>(transformedData,
Dynamic\Transforms\Concatenate.cs (2)
39var dataview = mlContext.Data.LoadFromEnumerable(samples); 60var featuresColumn = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\Conversion\ConvertType.cs (2)
20var data = mlContext.Data.LoadFromEnumerable(rawData); 32var convertedData = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\Conversion\ConvertTypeMultiColumn.cs (2)
37var data = mlContext.Data.LoadFromEnumerable(rawData); 57var convertedData = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\Conversion\Hash.cs (2)
25var data = mlContext.Data.LoadFromEnumerable(rawData); 54var convertedData = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\Conversion\HashWithOptions.cs (2)
27var data = mlContext.Data.LoadFromEnumerable(rawData); 68var convertedData = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\Conversion\KeyToValueToKey.cs (3)
26var trainData = mlContext.Data.LoadFromEnumerable(rawData); 56IEnumerable<TransformedData> defaultData = mlContext.Data. 60IEnumerable<TransformedData> customizedData = mlContext.Data.
Dynamic\Transforms\Conversion\MapKeyToBinaryVector.cs (2)
32var data = mlContext.Data.LoadFromEnumerable(rawData); 43IEnumerable<TransformedData> features = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\Conversion\MapKeyToValueMultiColumn.cs (3)
27var dataView = mlContext.Data.LoadFromEnumerable(examples); 58transformedData = mlContext.Data.TakeRows(transformedData, 5); 59var values = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\Conversion\MapKeyToVector.cs (2)
29var data = mlContext.Data.LoadFromEnumerable(rawData); 56IEnumerable<TransformedData> features = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\Conversion\MapKeyToVectorMultiColumn.cs (2)
31var data = mlContext.Data.LoadFromEnumerable(rawData); 44IEnumerable<TransformedData> features = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\Conversion\MapValue.cs (2)
28var data = mlContext.Data.LoadFromEnumerable(rawData); 71IEnumerable<TransformedData> features = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\Conversion\MapValueIdvLookup.cs (3)
29var data = mlContext.Data.LoadFromEnumerable(rawData); 42var lookupIdvMap = mlContext.Data.LoadFromEnumerable(lookupData); 54IEnumerable<TransformedData> features = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\Conversion\MapValueToArray.cs (2)
31var data = mlContext.Data.LoadFromEnumerable(rawData); 51IEnumerable<TransformedData> featuresColumn = mlContext.Data
Dynamic\Transforms\Conversion\MapValueToKeyMultiColumn.cs (4)
27var data = mlContext.Data.LoadFromEnumerable(rawData); 42IEnumerable<TransformedData> features = mlContext.Data.CreateEnumerable< 78var lookupIdvMap = mlContext.Data.LoadFromEnumerable(lookupData); 93features = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\CopyColumns.cs (2)
38var dataview = mlContext.Data.LoadFromEnumerable(samples); 56var rowEnumerable = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\CustomMapping.cs (2)
27var data = mlContext.Data.LoadFromEnumerable(samples); 47var dataEnumerable = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\CustomMappingSaveAndLoad.cs (2)
30var data = mlContext.Data.LoadFromEnumerable(samples); 63var dataEnumerable = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\CustomMappingWithInMemoryCustomType.cs (2)
29var tribeDataView = mlContext.Data.LoadFromEnumerable(tribe); 37var firstAlien = mlContext.Data.CreateEnumerable<SuperAlienHero>(
Dynamic\Transforms\DropColumns.cs (3)
38var dataview = mlContext.Data.LoadFromEnumerable(samples); 56var failingRowEnumerable = mlContext.Data.CreateEnumerable< 71var rowEnumerable = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\Expression.cs (2)
29var dataview = mlContext.Data.LoadFromEnumerable(samples); 47var featuresColumn = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnCount.cs (2)
31var data = mlContext.Data.LoadFromEnumerable(rawData); 46var convertedData = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnCountMultiColumn.cs (2)
31var data = mlContext.Data.LoadFromEnumerable(rawData); 46var convertedData = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnMutualInformation.cs (2)
31var data = mlContext.Data.LoadFromEnumerable(rawData); 44var convertedData = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnMutualInformationMultiColumn.cs (2)
31var data = mlContext.Data.LoadFromEnumerable(rawData); 47var convertedData = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\ImageAnalytics\ConvertToGrayScale.cs (1)
34var data = mlContext.Data.CreateTextLoader(new TextLoader.Options()
Dynamic\Transforms\ImageAnalytics\ConvertToGrayScaleInMemory.cs (2)
21var data = mlContext.Data.LoadFromEnumerable(images); 33var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\ImageAnalytics\ConvertToImage.cs (1)
29var data = mlContext.Data.LoadFromEnumerable(dataPoints);
Dynamic\Transforms\ImageAnalytics\DnnFeaturizeImage.cs (1)
33var data = mlContext.Data.CreateTextLoader(new TextLoader.Options()
Dynamic\Transforms\ImageAnalytics\ExtractPixels.cs (1)
36var data = mlContext.Data.CreateTextLoader(new TextLoader.Options()
Dynamic\Transforms\ImageAnalytics\LoadImages.cs (1)
33var data = mlContext.Data.CreateTextLoader(new TextLoader.Options()
Dynamic\Transforms\ImageAnalytics\ResizeImages.cs (1)
33var data = mlContext.Data.CreateTextLoader(new TextLoader.Options()
Dynamic\Transforms\IndicateMissingValues.cs (2)
24var data = mlContext.Data.LoadFromEnumerable(samples); 40var rowEnumerable = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\IndicateMissingValuesMultiColumn.cs (2)
28var data = mlContext.Data.LoadFromEnumerable(samples); 48var rowEnumerable = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\NormalizeBinning.cs (1)
28var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeBinningMulticolumn.cs (1)
34var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeGlobalContrast.cs (1)
25var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeLogMeanVariance.cs (1)
27var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeLogMeanVarianceFixZero.cs (1)
26var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeLpNorm.cs (1)
26var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeMeanVariance.cs (1)
27var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeMinMax.cs (1)
25var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeMinMaxMulticolumn.cs (1)
42var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\NormalizeSupervisedBinning.cs (1)
37var data = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Projection\VectorWhiten.cs (1)
22var trainData = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\Projection\VectorWhitenWithOptions.cs (1)
21var trainData = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\ReplaceMissingValues.cs (3)
28var data = mlContext.Data.LoadFromEnumerable(samples); 44var defaultRowEnumerable = mlContext.Data.CreateEnumerable< 75var meanRowEnumerable = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\ReplaceMissingValuesMultiColumn.cs (3)
32var data = mlContext.Data.LoadFromEnumerable(samples); 50var defaultRowEnumerable = mlContext.Data.CreateEnumerable< 86var meanRowEnumerable = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\SelectColumns.cs (2)
38var dataview = mlContext.Data.LoadFromEnumerable(samples); 58var rowEnumerable = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\StatefulCustomMapping.cs (2)
28var data = mlContext.Data.LoadFromEnumerable(samples); 61var dataEnumerable = mlContext.Data.CreateEnumerable<TransformedData>(
Dynamic\Transforms\Text\ApplyCustomWordEmbedding.cs (1)
23var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);
Dynamic\Transforms\Text\ApplyWordEmbedding.cs (1)
23var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);
Dynamic\Transforms\Text\FeaturizeText.cs (1)
39var dataview = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Text\FeaturizeTextWithOptions.cs (1)
40var dataview = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Text\LatentDirichletAllocation.cs (1)
33var dataview = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Text\NormalizeText.cs (1)
23var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);
Dynamic\Transforms\Text\ProduceHashedNgrams.cs (1)
37var dataview = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Text\ProduceHashedWordBags.cs (1)
40var dataview = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Text\ProduceNgrams.cs (1)
44var dataview = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Text\ProduceWordBags.cs (1)
49var dataview = mlContext.Data.LoadFromEnumerable(samples);
Dynamic\Transforms\Text\RemoveDefaultStopWords.cs (1)
24var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);
Dynamic\Transforms\Text\RemoveStopWords.cs (1)
23var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);
Dynamic\Transforms\Text\TokenizeIntoCharactersAsKeys.cs (1)
23var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);
Dynamic\Transforms\Text\TokenizeIntoWords.cs (1)
23var emptyDataView = mlContext.Data.LoadFromEnumerable(emptySamples);
Dynamic\Transforms\TimeSeries\DetectAnomalyBySrCnn.cs (1)
34var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TimeSeries\DetectAnomalyBySrCnnBatchPrediction.cs (2)
30var dataView = ml.Data.LoadFromEnumerable(data); 43var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>(
Dynamic\Transforms\TimeSeries\DetectChangePointBySsa.cs (1)
50var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TimeSeries\DetectChangePointBySsaBatchPrediction.cs (2)
54var dataView = ml.Data.LoadFromEnumerable(data); 67var predictionColumn = ml.Data.CreateEnumerable<ChangePointPrediction>(
Dynamic\Transforms\TimeSeries\DetectChangePointBySsaStream.cs (1)
50var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TimeSeries\DetectEntireAnomalyBySrCnn.cs (2)
31var dataView = ml.Data.LoadFromEnumerable(data); 43var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>(
Dynamic\Transforms\TimeSeries\DetectIidChangePoint.cs (1)
50var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TimeSeries\DetectIidChangePointBatchPrediction.cs (2)
48var dataView = ml.Data.LoadFromEnumerable(data); 61var predictionColumn = ml.Data.CreateEnumerable<ChangePointPrediction>(
Dynamic\Transforms\TimeSeries\DetectIidSpike.cs (1)
42var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TimeSeries\DetectIidSpikeBatchPrediction.cs (2)
40var dataView = ml.Data.LoadFromEnumerable(data); 52var predictionColumn = ml.Data.CreateEnumerable<IidSpikePrediction>(
Dynamic\Transforms\TimeSeries\DetectSeasonality.cs (1)
21var dataView = mlContext.Data.LoadFromEnumerable(seasonalData);
Dynamic\Transforms\TimeSeries\DetectSpikeBySsa.cs (1)
48var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TimeSeries\DetectSpikeBySsaBatchPrediction.cs (2)
56var dataView = ml.Data.LoadFromEnumerable(data); 69var predictionColumn = ml.Data.CreateEnumerable<SsaSpikePrediction>(
Dynamic\Transforms\TimeSeries\Forecasting.cs (1)
42var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TimeSeries\ForecastingWithConfidenceInterval.cs (1)
42var dataView = ml.Data.LoadFromEnumerable(data);
Dynamic\Transforms\TreeFeaturization\FastForestBinaryFeaturizationWithOptions.cs (3)
27var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 35dataView = mlContext.Data.Cache(dataView); 82var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\TreeFeaturization\FastForestRegressionFeaturizationWithOptions.cs (3)
27var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 35dataView = mlContext.Data.Cache(dataView); 83var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\TreeFeaturization\FastTreeBinaryFeaturizationWithOptions.cs (3)
27var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 35dataView = mlContext.Data.Cache(dataView); 84var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\TreeFeaturization\FastTreeRankingFeaturizationWithOptions.cs (3)
27var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 35dataView = mlContext.Data.Cache(dataView); 80var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\TreeFeaturization\FastTreeRegressionFeaturizationWithOptions.cs (3)
27var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 35dataView = mlContext.Data.Cache(dataView); 83var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\TreeFeaturization\FastTreeTweedieFeaturizationWithOptions.cs (3)
27var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 35dataView = mlContext.Data.Cache(dataView); 83var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\Transforms\TreeFeaturization\PretrainedTreeEnsembleFeaturizationWithOptions.cs (2)
27var dataView = mlContext.Data.LoadFromEnumerable(dataPoints); 73var transformedDataPoints = mlContext.Data.CreateEnumerable<
Dynamic\WithOnFitDelegate.cs (1)
36var data = mlContext.Data.LoadFromEnumerable(samples);
Microsoft.ML.Samples.GPU (15)
docs\samples\Microsoft.ML.Samples\Dynamic\TensorFlow\ImageClassification.cs (2)
39var idv = mlContext.Data.LoadFromEnumerable(data); 52var outScores = mlContext.Data.CreateEnumerable<OutputScores>(
docs\samples\Microsoft.ML.Samples\Dynamic\TensorFlow\TextClassification.cs (2)
42var dataView = mlContext.Data.LoadFromEnumerable(data); 45var lookupMap = mlContext.Data.LoadFromTextFile(Path.Combine(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (3)
43IDataView shuffledFullImagesDataset = mlContext.Data.ShuffleRows( 44mlContext.Data.LoadFromEnumerable(images)); 58TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\LearningRateSchedulingCifarResnetTransferLearning.cs (2)
47IDataView trainDataset = mlContext.Data. 66IDataView testDataset = mlContext.Data.
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (3)
42IDataView shuffledFullImagesDataset = mlContext.Data.ShuffleRows( 43mlContext.Data.LoadFromEnumerable(images)); 57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (3)
42IDataView shuffledFullImagesDataset = mlContext.Data.ShuffleRows( 43mlContext.Data.LoadFromEnumerable(images)); 57TrainTestData trainTestData = mlContext.Data.TrainTestSplit(
Microsoft.ML.Samples.OneDal (1)
Program.cs (1)
39var loader = mlContext.Data.CreateTextLoader(
Microsoft.ML.SamplesUtils (2)
SamplesDatasetUtils.cs (2)
50var loader = mlContext.Data.CreateTextLoader( 126var loader = mlContext.Data.CreateTextLoader(
Microsoft.ML.TensorFlow.Tests (40)
TensorFlowEstimatorTests.cs (8)
64var dataView = ML.Data.LoadFromEnumerable( 84var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 85var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData); 86var invalidDataWrongVectorSize = ML.Data.LoadFromEnumerable(sizeData); 105var dataView = ML.Data.LoadFromEnumerable( 156var data = ML.Data.LoadFromTextFile(dataFile, new[] { 198var data = ML.Data.LoadFromTextFile(dataFile, new[] { 249var data = ML.Data.LoadFromTextFile(dataFile, new[] {
TensorflowTests.cs (32)
188var loader = _mlContext.Data.LoadFromEnumerable( 287var loader = _mlContext.Data.LoadFromEnumerable(data); 409var loader = _mlContext.Data.LoadFromEnumerable(data); 541var reader = _mlContext.Data.CreateTextLoader( 654var reader = _mlContext.Data.CreateTextLoader( 698var reader = _mlContext.Data.CreateTextLoader(columns: new[] 787var reader = _mlContext.Data.CreateTextLoader(new[] 880var reader = _mlContext.Data.CreateTextLoader(columns: new[] 1011var data = _mlContext.Data.LoadFromTextFile(dataFile, 1070var data = _mlContext.Data.LoadFromTextFile(dataFile, columns: new[] 1115var dataView = _mlContext.Data.LoadFromEnumerable<InMemoryImage>(dataObjects); 1223var data = _mlContext.Data.LoadFromTextFile(dataFile, 1264var dataView = _mlContext.Data.LoadFromEnumerable(data); 1266var lookupMap = _mlContext.Data.LoadFromTextFile(@"sentiment_model/imdb_word_index.csv", 1348var dataview = _mlContext.Data.CreateTextLoader<TextInput>().Load(new MultiFileSource(null)); 1377var dataview = _mlContext.Data.CreateTextLoader<PrimitiveInput>().Load(new MultiFileSource(null)); 1403IDataView shuffledFullImagesDataset = _mlContext.Data.ShuffleRows( 1404_mlContext.Data.LoadFromEnumerable(images), seed: 1); 1412TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1478IDataView shuffledFullImagesDataset = _mlContext.Data.ShuffleRows( 1479_mlContext.Data.LoadFromEnumerable(images), seed: 1); 1487TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1610IDataView shuffledFullImagesDataset = _mlContext.Data.ShuffleRows( 1611_mlContext.Data.LoadFromEnumerable(images), seed: 1); 1619TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1765IDataView shuffledFullImagesDataset = _mlContext.Data.ShuffleRows( 1766_mlContext.Data.LoadFromEnumerable(images), seed: 1); 1774TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 1854IDataView shuffledFullImagesDataset = _mlContext.Data.ShuffleRows( 1855_mlContext.Data.LoadFromEnumerable(images), seed: 1); 1864TrainTestData trainTestData = _mlContext.Data.TrainTestSplit( 2053IDataView data = _mlContext.Data.LoadFromTextFile(dataFile, new[] {
Microsoft.ML.TestFramework (5)
DataPipe\TestDataPipeBase.cs (1)
424var loadedData = ML.Data.LoadFromTextFile(pathData, options: args);
TestSparseDataView.cs (4)
51var data = env.Data.LoadFromEnumerable(inputs); 65var iter = env.Data.CreateEnumerable<SparseExample<T>>(data, false).GetEnumerator(); 91var data = env.Data.LoadFromEnumerable(inputs); 105var iter = env.Data.CreateEnumerable<DenseExample<T>>(data, false).GetEnumerator();
Microsoft.ML.Tests (577)
AnomalyDetectionTests.cs (6)
151var data = mlContext.Data.LoadFromEnumerable(samples); 160var results = mlContext.Data.CreateEnumerable<Result>(transformed, reuseRowObject: false).ToList(); 195var data = mlContext.Data.LoadFromEnumerable(samples); 206var results = mlContext.Data.CreateEnumerable<Result>(transformed, reuseRowObject: false).ToList(); 239var loader = ML.Data.CreateTextLoader(new[] 275var data = mlContext.Data.LoadFromEnumerable(samples);
BinaryLoaderSaverTests.cs (2)
24var data = ML.Data.LoadFromBinary(GetDataPath("schema-codec-test.idv")); 30ML.Data.SaveAsText(data, fs, headerRow: false);
CachingTests.cs (5)
49pipe.Fit(ML.Data.LoadFromEnumerable(trainData)); 59pipe.Fit(ML.Data.LoadFromEnumerable(trainData)); 84var data = ML.Data.LoadFromEnumerable(src); 90data = ML.Data.LoadFromEnumerable(src); 91data = ML.Data.Cache(data);
CollectionsDataViewTest.cs (18)
160var dataView = env.Data.LoadFromEnumerable(data); 161var enumeratorSimple = env.Data.CreateEnumerable<ConversionSimpleClass>(dataView, false).GetEnumerator(); 191var dataView = env.Data.LoadFromEnumerable(data); 192var enumerator = env.Data.CreateEnumerable<ConversionNotSupportedMinValueClass>(dataView, false).GetEnumerator(); 234var dataView = env.Data.LoadFromEnumerable(data); 235var enumeratorSimple = env.Data.CreateEnumerable<ClassWithConstField>(dataView, false).GetEnumerator(); 260var dataView = env.Data.LoadFromEnumerable(data); 261var enumeratorSimple = env.Data.CreateEnumerable<ClassWithMixOfFieldsAndProperties>(dataView, false).GetEnumerator(); 314var dataView = env.Data.LoadFromEnumerable(data); 315var enumeratorSimple = env.Data.CreateEnumerable<ClassWithPrivateFieldsAndProperties>(dataView, false).GetEnumerator(); 344var dataView = env.Data.LoadFromEnumerable(data); 345var enumeratorSimple = env.Data.CreateEnumerable<ClassWithInheritedProperties>(dataView, false).GetEnumerator(); 395var dataView = env.Data.LoadFromEnumerable(data); 396var enumeratorSimple = env.Data.CreateEnumerable<ClassWithArrays>(dataView, false).GetEnumerator(); 446var dataView = env.Data.LoadFromEnumerable(data); 447var enumeratorSimple = env.Data.CreateEnumerable<ClassWithArrayProperties>(dataView, false).GetEnumerator(); 483var dataView = env.Data.LoadFromEnumerable(data); 484var enumeratorSimple = env.Data.CreateEnumerable<ClassWithSetter>(dataView, false).GetEnumerator();
DatabaseLoaderTests.cs (6)
63var loader = mlContext.Data.CreateDatabaseLoader(loaderColumns); 99var loader = mlContext.Data.CreateDatabaseLoader<IrisDataWithLoadColumnName>(); 135var loader = mlContext.Data.CreateDatabaseLoader<IrisVectorData>(); 167var loader = mlContext.Data.CreateDatabaseLoader<IrisVectorDataWithLoadColumnName>(); 199var loader = mlContext.Data.CreateDatabaseLoader<IrisData>(); 258var loader = mlContext.Data.CreateDatabaseLoader(new DatabaseLoader.Column("datetime", DbType.DateTime, 0));
EvaluateTests.cs (2)
47var inputDV = mlContext.Data.LoadFromEnumerable(inputArray); 64var inputDV2 = mlContext.Data.LoadFromEnumerable(inputArray2);
FeatureContributionTests.cs (3)
243var savedData = ML.Data.TakeRows(estimator.Fit(data).Transform(data), 4); 418IDataView trainingDataView = ML.Data.LoadFromTextFile<TaxiTrip>(trainDataPath, hasHeader: true, separatorChar: ','); 434var someRows = ML.Data.TakeRows(trainingDataView, numberOfInstances);
ImagesTests.cs (5)
236var data = ML.Data.LoadFromEnumerable(images); 248var transformedDataPoints = ML.Data.CreateEnumerable<ImageDataPoint>(transformedData, false); 1091var data = mlContext.Data.LoadFromEnumerable(dataPoints); 1129var tsvFile = mlContext.Data.LoadFromTextFile(tsvPath, columns: new[] 1182var dataView = mlContext.Data.LoadFromEnumerable<InMemoryImage>(dataObjects);
OnnxConversionTest.cs (53)
71var data = mlContext.Data.LoadFromTextFile<AdultData>(trainDataPath, 75var cachedTrainData = mlContext.Data.Cache(data); 149var data = mlContext.Data.LoadFromTextFile<BreastCancerFeatureVector>(dataPath, 182var dataView = mlContext.Data.LoadFromTextFile<AdultData>(dataPath, 222var dataView = mlContext.Data.LoadFromTextFile<BreastCancerBinaryClassification>(dataPath, separatorChar: '\t', hasHeader: false); 262var dataView = mlContext.Data.LoadFromTextFile(dataPath, new[] { 280var dataView = ML.Data.LoadFromTextFile<BreastCancerBinaryClassification>(dataPath, separatorChar: '\t', hasHeader: true); 319IDataView dataSoloCalibrator = ML.Data.LoadFromEnumerable(GetCalibratorTestData()); 324IDataView dataSoloCalibratorNonStandard = ML.Data.LoadFromEnumerable(GetCalibratorTestDataNonStandard()); 386var dataView = ML.Data.LoadFromTextFile(dataPath, new[] { 423var dataView = mlContext.Data.LoadFromEnumerable(samples); 477mlContext.Data.LoadFromTextFile(filePath, columnsScalar, separatorChar: '\t'), //scalar 478mlContext.Data.LoadFromTextFile(filePath, columnsVector , separatorChar: '\t') //vector 567var data = mlContext.Data.LoadFromTextFile<AdultData>(trainDataPath, 571var cachedTrainData = mlContext.Data.Cache(data); 598var data = mlContext.Data.LoadFromTextFile<AdultData>(trainDataPath, 602var cachedTrainData = mlContext.Data.Cache(data); 624var data = mlContext.Data.LoadFromTextFile<BreastCancerMulticlassExample>(dataPath, 769var data = ML.Data.LoadFromTextFile(dataPath, new[] { 788var data = mlContext.Data.LoadFromTextFile<BreastCancerCatFeatureExample>(dataPath, 851var data = mlContext.Data.LoadFromTextFile<SmallSentimentExample>(dataPath, separatorChar: '\t', hasHeader: false); 870var dataView = ML.Data.LoadFromTextFile(dataPath, new[] { 947var dataView = mlContext.Data.LoadFromTextFile(filePath, columns); 967var dataView = mlContext.Data.LoadFromTextFile(dataSource, new[] { 1004var dataView = mlContext.Data.LoadFromTextFile<BreastCancerCatFeatureExample>(dataPath); 1034var data = ML.Data.LoadFromTextFile(dataFile, new[] 1074var dataView = mlContext.Data.LoadFromTextFile(dataPath, new[] { 1125var dataView = mlContext.Data.LoadFromTextFile(dataPath, new[] { 1160var dataView = mlContext.Data.LoadFromEnumerable(samples); 1202mlContext.Data.LoadFromTextFile(filePath, columnsScalar, separatorChar: '\t'), //scalar 1203mlContext.Data.LoadFromTextFile(filePath, columnsVector , separatorChar: '\t') //vector 1240mlContext.Data.LoadFromTextFile(filePath, columnsScalar, separatorChar: '\t'), //scalar 1241mlContext.Data.LoadFromTextFile(filePath, columnsVector , separatorChar: '\t') //vector 1404mlContext.Data.LoadFromTextFile(filePath, columnsScalar, separatorChar: '\t'), //scalar 1405mlContext.Data.LoadFromTextFile(filePath, columnsVector , separatorChar: '\t') //vector 1446var dataView = mlContext.Data.LoadFromEnumerable(samples); 1474var dataView = mlContext.Data.LoadFromEnumerable(samples); 1552var dataView = mlContext.Data.LoadFromEnumerable(samples); 1576var dataView = mlContext.Data.LoadFromEnumerable(samples); 1603var dataView = ML.Data.LoadFromTextFile(dataPath, new[] { 1647var dataView = mlContext.Data.LoadFromTextFile<BreastCancerMulticlassExample>(dataPath, separatorChar: '\t', hasHeader: false); 1701var dataView = mlContext.Data.LoadFromTextFile<AdultData>(trainDataPath, 1719var dataView = mlContext.Data.LoadFromTextFile<AdultData>(trainDataPath, 1762var loader = mlContext.Data.CreateTextLoader( 1781mlContext.Data.SaveAsBinary(mappedData, stream, keepHidden: false); 1788IDataView reloadedData = mlContext.Data.LoadFromBinary(mappedDataPath); 1847var dataView = mlContext.Data.LoadFromTextFile(dataPath, new[] { 1886var dataView = ML.Data.LoadFromTextFile(dataPath, new[] { 1933var dataView = mlContext.Data.LoadFromTextFile<BreastCancerBinaryClassificationNonDefaultColNames>(dataPath, separatorChar: '\t', hasHeader: false); 1974var dataView = mlContext.Data.LoadFromTextFile<BreastCancerMulticlassExampleNonDefaultColNames>(dataPath, separatorChar: '\t', hasHeader: false); 2025var dataView = ML.Data.LoadFromTextFile<BreastCancerCatFeatureExample>(dataPath); 2186var dataView = ML.Data.LoadFromEnumerable(data, schemaDefinition); 2223var dataView = ML.Data.LoadFromEnumerable(data, schemaDefinition);
OnnxSequenceTypeWithAttributesTest.cs (2)
44var dataView = ctx.Data.LoadFromEnumerable(new List<FloatInput>()); 83var dataView = ctx.Data.LoadFromEnumerable(new List<FloatInput>());
PermutationFeatureImportanceTests.cs (1)
489var data = ML.Data.LoadFromTextFile(dataPath,
RangeFilterTests.cs (2)
27var data1 = ML.Data.FilterRowsByColumn(data, "Floats", upperBound: 2.8); 32var data2 = ML.Data.FilterRowsByKeyColumnFraction(data, "Key", upperBound: 0.15);
Scenarios\Api\CookbookSamples\CookbookSamplesDynamicApi.cs (22)
41var data = mlContext.Data.LoadFromTextFile<InspectedRow>(dataPath, 56.Data.CreateEnumerable<InspectedRowWithAllFeatures>(transformedData, reuseRowObject: false) 94var data = mlContext.Data.LoadFromEnumerable(samples); 151var trainData = mlContext.Data.LoadFromTextFile<RegressionData>(trainDataPath, 162var cachedTrainData = mlContext.Data.Cache(trainData); 187var testData = mlContext.Data.LoadFromTextFile<RegressionData>(testDataPath, 219var trainData = mlContext.Data.LoadFromTextFile<IrisInput>(irisDataPath, 304var trainData = mlContext.Data.LoadFromTextFile<IrisInputAllFeatures>(dataPath, 334IDataView data = context.Data.LoadFromTextFile(dataPath, new[] 374IDataView data = context.Data.LoadFromTextFile(dataPath, new[] 409IDataView data = context.Data.LoadFromTextFile(dataPath, new[] 445IDataView data = context.Data.LoadFromTextFile(dataPath, new[] 476var shuffledSubset = context.Data.TakeRows(context.Data.ShuffleRows(featureContributionData), 10); 477var scoringEnumerator = context.Data.CreateEnumerable<HousingData>(shuffledSubset, true); 504var loader = mlContext.Data.CreateTextLoader(new[] 573var loader = mlContext.Data.CreateTextLoader(new[] 636var data = mlContext.Data.LoadFromTextFile<IrisInput>(dataPath, 655var split = mlContext.Data.TrainTestSplit(data, testFraction: 0.1); 685var loader = mlContext.Data.LoadFromTextFile<RegressionData>(dataPath, 706var data = mlContext.Data.LoadFromTextFile(GetDataPath("adult.tiny.with-schema.txt"), new[] 746var cachedTrainData = mlContext.Data.Cache(trainData);
Scenarios\Api\Estimators\DecomposableTrainAndPredict.cs (3)
31var data = ml.Data.LoadFromTextFile<IrisData>(dataPath, separatorChar: ','); 42var testLoader = ml.Data.LoadFromTextFile(dataPath, TestDatasets.irisData.GetLoaderColumns(), separatorChar: ',', hasHeader: true); 43var testData = ml.Data.CreateEnumerable<IrisData>(testLoader, false);
Scenarios\Api\Estimators\Extensibility.cs (3)
30var data = ml.Data.CreateTextLoader(TestDatasets.irisData.GetLoaderColumns(), separatorChar: ',') 51var testLoader = ml.Data.LoadFromTextFile(dataPath, TestDatasets.irisData.GetLoaderColumns(), separatorChar: ','); 52var testData = ml.Data.CreateEnumerable<IrisData>(testLoader, false);
Scenarios\Api\Estimators\MultithreadedPrediction.cs (3)
28var data = ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.trainFilename), hasHeader: true); 43var testData = ml.Data.CreateEnumerable<SentimentData>( 44ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.testFilename), hasHeader: true), false);
Scenarios\Api\Estimators\PredictAndMetadata.cs (5)
29var data = ml.Data.LoadFromTextFile<IrisData>(dataPath, separatorChar: ','); 39var testLoader = ml.Data.LoadFromTextFile(dataPath, TestDatasets.irisData.GetLoaderColumns(), separatorChar: ',', hasHeader: true); 40var testData = ml.Data.CreateEnumerable<IrisData>(testLoader, false); 78var data = mlContext.Data.LoadFromTextFile<IrisData>(dataPath, separatorChar: ','); 99var dataReader = mlContext.Data.CreateTextLoader(
Scenarios\Api\Estimators\SimpleTrainAndPredict.cs (6)
26var data = ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.trainFilename), hasHeader: true); 41var testData = ml.Data.CreateEnumerable<SentimentData>( 42ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.testFilename), hasHeader: true), false); 63var data = ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.trainFilename), hasHeader: true); 80var testData = ml.Data.CreateEnumerable<SentimentData>( 81ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.testFilename), hasHeader: true), false);
Scenarios\Api\Estimators\TrainWithInitialPredictor.cs (2)
25var data = ml.Data.LoadFromTextFile<SentimentData>(GetDataPath(TestDatasets.Sentiment.trainFilename), hasHeader: true); 32var trainData = ml.Data.Cache(pipeline.Fit(data).Transform(data));
Scenarios\Api\TestApi.cs (29)
69var idv1 = env.Data.LoadFromEnumerable(data1); 82var idv2 = env.Data.LoadFromEnumerable(data2); 103var idv3 = env.Data.LoadFromEnumerable(data3); 128var idv4 = env.Data.LoadFromEnumerable(Utils.CreateArray(10, example4)); 153var idv = env.Data.LoadFromEnumerable(data); 161var applied = env.Data.LoadFromEnumerable(data); 183var cached = mlContext.Data.Cache(xf); 229var idv = mlContext.Data.LoadFromEnumerable(data, autoSchema); 301var fullInput = mlContext.Data.LoadFromTextFile(dataPath, new[] { 308var ttSplit = mlContext.Data.TrainTestSplit(fullInput); 309var ttSplitWithSeed = mlContext.Data.TrainTestSplit(fullInput, seed: 10); 310var ttSplitWithSeedAndSamplingKey = mlContext.Data.TrainTestSplit(fullInput, seed: 10, samplingKeyColumnName: "Workclass"); 312var cvSplit = mlContext.Data.CrossValidationSplit(fullInput); 313var cvSplitWithSeed = mlContext.Data.CrossValidationSplit(fullInput, seed: 10); 314var cvSplitWithSeedAndSamplingKey = mlContext.Data.CrossValidationSplit(fullInput, seed: 10, samplingKeyColumnName: "Workclass"); 349var input = mlContext.Data.LoadFromTextFile(dataPath, new[] { 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); 419var input = mlContext.Data.LoadFromEnumerable(new[] 456var split = mlContext.Data.TrainTestSplit(input, 0.5, nameof(Input.TextStrat)); 460split = mlContext.Data.TrainTestSplit(input, 0.5, nameof(Input.FloatStrat)); 464split = mlContext.Data.TrainTestSplit(input, 0.5, nameof(Input.VectorStrat)); 468split = mlContext.Data.TrainTestSplit(input, 0.5, nameof(Input.DateTimeStrat)); 472split = mlContext.Data.TrainTestSplit(input, 0.5, nameof(Input.DateTimeOffsetStrat)); 476split = mlContext.Data.TrainTestSplit(input, 0.5, nameof(Input.TimeSpanStrat)); 482split = mlContext.Data.TrainTestSplit(inputWithKey, 0.5, "KeyStrat"); 500var cvSplits = mlContext.Data.CrossValidationSplit(inputWithKey, numberOfFolds: 2, samplingKeyColumnName: colname);
Scenarios\ClusteringTests.cs (2)
62var trainData = mlContext.Data.LoadFromEnumerable(data); 63var testData = mlContext.Data.LoadFromEnumerable(clusters);
Scenarios\GetColumnTests.cs (3)
29var data = mlContext.Data.LoadFromTextFile(path, new[] { 52var data1 = mlContext.Data.LoadFromTextFile(path, new[] { 71var data = mlContext.Data.LoadFromTextFile(path, new[] {
Scenarios\IrisPlantClassificationTests.cs (1)
22var reader = mlContext.Data.CreateTextLoader(columns: new[]
Scenarios\IrisPlantClassificationWithStringLabelTests.cs (1)
18var reader = mlContext.Data.CreateTextLoader(columns: new[]
Scenarios\OvaTest.cs (4)
32var data = mlContext.Data.Cache(mlContext.Transforms.Conversion.MapValueToKey("Label") 66var data = mlContext.Data.Cache(mlContext.Transforms.Conversion.MapValueToKey("Label") 102var data = mlContext.Data.Cache(mlContext.Transforms.Conversion.MapValueToKey("Label") 136var data = mlContext.Data.Cache(mlContext.Transforms.Conversion.MapValueToKey("Label")
Scenarios\RegressionTest.cs (3)
20context.Data.LoadFromTextFile<FeatureContributionTests.TaxiTrip>(taxiDataPath, hasHeader: true, 23var splitData = context.Data.TrainTestSplit(taxiData, testFraction: 0.1); 25IDataView trainingDataView = context.Data.FilterRowsByColumn(splitData.TrainSet, "FareAmount", lowerBound: 1, upperBound: 150);
Scenarios\WordBagTest.cs (2)
30var dataview = mlContext.Data.LoadFromEnumerable(samples); 67var dataview = mlContext.Data.LoadFromEnumerable(samples);
ScenariosWithDirectInstantiation\IrisPlantClassificationTests.cs (1)
20var reader = mlContext.Data.CreateTextLoader(columns: new[]
SvmLightTests.cs (37)
43var data = ML.Data.LoadFromSvmLightFile(path, inputSize: inputSize, zeroBased: zeroBased, numberOfRows: numberOfRows); 50ML.Data.SaveInSvmLightFormat(expectedData, stream, zeroBasedIndexing: zeroBased, exampleWeightColumnName: "Weight"); 51data = ML.Data.LoadFromSvmLightFile(savingPath, inputSize: inputSize, zeroBased: zeroBased); 77var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 105var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 134var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 155var model = ML.Data.CreateSvmLightLoaderWithFeatureNames(dataSample: new MultiFileSource(path)); 164var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 175ML.Data.SaveInSvmLightFormat(expectedData, stream, zeroBasedIndexing: true, rowGroupColumnName: "GroupId"); 176data = ML.Data.LoadFromSvmLightFile(outputPath, zeroBased: true); 188expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 198ML.Data.SaveInSvmLightFormat(expectedData, stream); 199data = ML.Data.LoadFromSvmLightFile(outputPath); 207var data = ML.Data.LoadFromSvmLightFileWithFeatureNames(path); 212var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 221ML.Data.SaveInSvmLightFormat(expectedData, stream, zeroBasedIndexing: true); 222data = ML.Data.LoadFromSvmLightFile(outputPath, zeroBased: true); 238var view = ML.Data.LoadFromSvmLightFileWithFeatureNames(path); 258var data = ML.Data.LoadFromSvmLightFile(path); 277var data = ML.Data.LoadFromSvmLightFile(path); 307var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 325var data = ML.Data.LoadFromSvmLightFile(path); 349var data = ML.Data.LoadFromSvmLightFile(path); 368data = ML.Data.LoadFromSvmLightFile(path); 387data = ML.Data.LoadFromSvmLightFile(path); 406ex = Assert.Throws<InvalidOperationException>(() => ML.Data.LoadFromSvmLightFile(path)); 419var loader = ML.Data.CreateSvmLightLoader(inputSize: 4); 432loader = ML.Data.CreateSvmLightLoader(inputSize: 3); 443var ex = Assert.Throws<InvalidOperationException>(() => ML.Data.CreateSvmLightLoader()); 445ex = Assert.Throws<InvalidOperationException>(() => ML.Data.CreateSvmLightLoaderWithFeatureNames()); 464var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 491var expectedData = ML.Data.LoadFromEnumerable(new SvmLightOutput[] 506var loader = ML.Data.CreateTextLoader(new[] { new TextLoader.Column("Column", DataKind.Single, 0) }); 511ML.Data.SaveInSvmLightFormat(loader.Load(new MultiFileSource(null)), stream); 519ML.Data.SaveInSvmLightFormat(loader.Load(new MultiFileSource(null)), stream, labelColumnName: "Column"); 527ML.Data.SaveInSvmLightFormat(loader.Load(new MultiFileSource(null)), stream, labelColumnName: "Column", featureColumnName: "Column", rowGroupColumnName: "Group"); 535ML.Data.SaveInSvmLightFormat(loader.Load(new MultiFileSource(null)), stream, labelColumnName: "Column", featureColumnName: "Column", exampleWeightColumnName: "Weight");
TermEstimatorTests.cs (6)
81data = ML.Data.TakeRows(data, 10); 101var dataView = ML.Data.LoadFromEnumerable(data); 107var invalidData = ML.Data.LoadFromEnumerable(xydata); 108var validFitNotValidTransformData = ML.Data.LoadFromEnumerable(stringData); 116var dataView = ML.Data.LoadFromEnumerable(data); 138var dataView = ML.Data.LoadFromEnumerable(data);
TextLoaderTests.cs (30)
584var ex = Assert.Throws<ArgumentOutOfRangeException>(() => mlContext.Data.LoadFromTextFile<ModelWithoutColumnAttribute>("fakefile.txt")); 597var data = mlContext.Data.LoadFromTextFile(combinedPath); 601var data2 = mlContext.Data.LoadFromTextFile<Input>(combinedPath); 611var loader = mlContext.Data.CreateTextLoader(new TextLoader.Options(), new MultiFileSource(fileName)); 746dataIris = mlContext.Data.CreateTextLoader<Iris>(new TextLoader.Options() { Separator = ",", AllowQuoting = false }).Load(dataPath); 748dataIris = mlContext.Data.CreateTextLoader<Iris>(separatorChar: ',').Load(dataPath); 767dataIrisStartEnd = mlContext.Data.CreateTextLoader<IrisStartEnd>(new TextLoader.Options() { Separator = ",", AllowQuoting = false }).Load(dataPath); 769dataIrisStartEnd = mlContext.Data.CreateTextLoader<IrisStartEnd>(separatorChar: ',').Load(dataPath); 789dataIrisColumnIndices = mlContext.Data.CreateTextLoader<IrisColumnIndices>(new TextLoader.Options() { Separator = ",", AllowQuoting = false }).Load(dataPath); 791dataIrisColumnIndices = mlContext.Data.CreateTextLoader<IrisColumnIndices>(separatorChar: ',').Load(dataPath); 1066dataViewPeriod = mlContext.Data.LoadFromTextFile(periodPath, optionsPeriod); 1068dataViewPeriod = mlContext.Data.LoadFromTextFile(commaPath, optionsPeriod); 1071dataViewComma = mlContext.Data.LoadFromTextFile(commaPath, optionsComma); 1073dataViewComma = mlContext.Data.LoadFromTextFile(periodPath, optionsComma); 1186var dataIris = mlContext.Data.CreateTextLoader<IrisPublicGetProperties>(separatorChar: ',').Load(dataPath); 1187var oneIrisData = mlContext.Data.CreateEnumerable<IrisPublicProperties>(dataIris, false).First(); 1191dataIris = mlContext.Data.CreateTextLoader<IrisPublicFields>(separatorChar: ',').Load(dataPath); 1192oneIrisData = mlContext.Data.CreateEnumerable<IrisPublicProperties>(dataIris, false).First(); 1198dataIris = mlContext.Data.CreateTextLoader<IrisNoFields>(separatorChar: ',').Load(dataPath); 1209dataIris = mlContext.Data.CreateTextLoader<IrisPrivateFields>(separatorChar: ',').Load(dataPath); 1244var data = mlContext.Data.CreateTextLoader<BreastCancerInputModelWithKeyType>(separatorChar: ',').Load(breastCancerPath); 1256var data = mlContext.Data.CreateTextLoader<BreastCancerInputModelWithoutKeyType>(separatorChar: ',').Load(breastCancerPath); 1292var data = mlContext.Data.LoadFromTextFile(dataPath, options); 1307mlContext.Data.SaveAsText(data, fs, separatorChar: '\t'); 1311data = mlContext.Data.LoadFromTextFile(savedPath, options); 1403var data = mlContext.Data.LoadFromTextFile(filePath, options); 1458baselineDV = mlContext.Data.LoadFromTextFile(baselineWithImpute, options); 1460testDV = mlContext.Data.LoadFromTextFile(inputPath, options); 1464baselineDV = mlContext.Data.LoadFromTextFile(baselineWithoutImpute, options); 1465testDV = mlContext.Data.LoadFromTextFile(inputPath, options);
TrainerEstimators\CalibratorEstimators.cs (3)
154mlContext.Data.LoadFromEnumerable<CalibratorTestInputReversedOrder>( 160mlContext.Data.LoadFromEnumerable<CalibratorTestInputUniqueScoreColumnName>( 166mlContext.Data.LoadFromEnumerable<CalibratorTestInputReversedOrderAndUniqueScoreColumnName>(
TrainerEstimators\FAFMEstimator.cs (2)
23var dataView = mlContext.Data.LoadFromEnumerable(data); 44var dataView = mlContext.Data.LoadFromEnumerable(data);
TrainerEstimators\MatrixFactorizationTests.cs (21)
212var dataView = ML.Data.LoadFromEnumerable(dataMatrix); 259var testDataView = mlContext.Data.LoadFromEnumerable(testMatrix); 262foreach (var pred in mlContext.Data.CreateEnumerable<MatrixElementForScore>(model.Transform(testDataView), false)) 323var dataView = ML.Data.LoadFromEnumerable(dataMatrix); 364foreach (var pred in mlContext.Data.CreateEnumerable<MatrixElementZeroBasedForScore>(prediction, false)) 379var invalidTestDataView = mlContext.Data.LoadFromEnumerable(invalidTestMatrix); 384foreach (var pred in mlContext.Data.CreateEnumerable<MatrixElementZeroBasedForScore>(invalidPrediction, false)) 443var dataView = ML.Data.LoadFromEnumerable(dataMatrix); 486var testDataView = ML.Data.LoadFromEnumerable(testDataMatrix); 491var testResults = mlContext.Data.CreateEnumerable<OneClassMatrixElementZeroBasedForScore>(testPrediction, false).ToList(); 558var testDataView = ML.Data.LoadFromEnumerable(testDataMatrix); 563var testResults = mlContext.Data.CreateEnumerable<OneClassMatrixElementZeroBasedForScore>(testPrediction, false).ToList(); 587var dataView = ML.Data.LoadFromEnumerable(dataMatrix); 628var testDataView = ML.Data.LoadFromEnumerable(testDataMatrix); 633var testResults = mlContext.Data.CreateEnumerable<OneClassMatrixElementZeroBasedForScore>(testPrediction, false).ToList(); 653var dataView = mlContext.Data.LoadFromEnumerable(data); 679var prediction = model.Transform(mlContext.Data.LoadFromEnumerable(testData)); 681var results = mlContext.Data.CreateEnumerable<OneClassMatrixElement>(prediction, false).ToList(); 770var dataView = ML.Data.LoadFromEnumerable(dataMatrix); 809var testData = ML.Data.LoadFromEnumerable(testMatrix); 815var predictions = mlContext.Data.CreateEnumerable<MatrixElementZeroBasedForScore256By256>(transformedTestData, false).ToList();
TrainerEstimators\OneDalEstimators.cs (1)
40var loader = ML.Data.CreateTextLoader(columns: new[] {
TrainerEstimators\OnlineLinearTests.cs (2)
20var regressionData = ML.Data.LoadFromTextFile(dataPath, new[] { 34var binaryData = ML.Data.LoadFromTextFile(dataPath, new[] {
TrainerEstimators\SdcaTests.cs (16)
21var data = ML.Data.LoadFromTextFile(dataPath, new[] { 26data = ML.Data.Cache(data); 67var data = mlContext.Data.LoadFromEnumerable(rawData); 71data = mlContext.Data.Cache(data); 88var rawPrediction = mlContext.Data.CreateEnumerable<SamplesUtils.DatasetUtils.CalibratedBinaryClassifierOutput>(prediction, false); 111var data = mlContext.Data.LoadFromEnumerable(rawData); 115data = mlContext.Data.Cache(data); 167var data = mlContext.Data.LoadFromEnumerable(rawData); 171data = mlContext.Data.Cache(data); 226var data = mlContext.Data.LoadFromEnumerable(rawData); 230data = mlContext.Data.Cache(data); 247var rawPrediction = mlContext.Data.CreateEnumerable<SamplesUtils.DatasetUtils.NonCalibratedBinaryClassifierOutput>(prediction, false); 268var data = mlContext.Data.LoadFromEnumerable(rawData); 272data = mlContext.Data.Cache(data); 303var data = mlContext.Data.LoadFromEnumerable(rawData); 307data = mlContext.Data.Cache(data);
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (28)
22var dataView = ML.Data.LoadFromEnumerable(data); 129var dataView = ML.Data.LoadFromEnumerable(data); 181var dataView = ML.Data.LoadFromEnumerable(data); 235var dataView = ML.Data.LoadFromEnumerable(data); 236dataView = ML.Data.Cache(dataView); 303var dataView = ML.Data.LoadFromEnumerable(data); 304dataView = ML.Data.Cache(dataView); 354var dataView = ML.Data.LoadFromEnumerable(data); 355dataView = ML.Data.Cache(dataView); 393var dataView = ML.Data.LoadFromEnumerable(data); 394dataView = ML.Data.Cache(dataView); 432var dataView = ML.Data.LoadFromEnumerable(data); 433dataView = ML.Data.Cache(dataView); 470var dataView = ML.Data.LoadFromEnumerable(data); 471dataView = ML.Data.Cache(dataView); 508var dataView = ML.Data.LoadFromEnumerable(data); 509dataView = ML.Data.Cache(dataView); 546var dataView = ML.Data.LoadFromEnumerable(data); 547dataView = ML.Data.Cache(dataView); 584var dataView = ML.Data.LoadFromEnumerable(data); 585dataView = ML.Data.Cache(dataView); 639var dataView = ML.Data.LoadFromEnumerable(data); 640dataView = ML.Data.Cache(dataView); 713var dataView = ML.Data.LoadFromEnumerable(data); 714dataView = ML.Data.Cache(dataView); 771var dataView = ML.Data.LoadFromEnumerable(data); 772dataView = ML.Data.Cache(dataView); 799var split = ML.Data.TrainTestSplit(dataView, 0.5);
TrainerEstimators\TreeEstimators.cs (7)
461var dataView = mlContext.Data.LoadFromEnumerable(dataList); 476mlnetPredictions = mlContext.Data.CreateEnumerable<GbmExample>(predicted, false).ToList(); 752var trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 759trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 766trainingData = mlContext.Data.LoadFromEnumerable(dataPoints); 875summaryDataEnumerable = ML.Data.CreateEnumerable<SummaryDataRow>(summaryDataView, false); 877summaryDataEnumerable = ML.Data.CreateEnumerable<QuantileTestSummaryDataRow>(summaryDataView, false);
Transformers\CategoricalHashTests.cs (8)
51var dataView = ML.Data.LoadFromEnumerable(data); 72ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 81var data = ML.Data.LoadFromTextFile(dataPath, new[] { 88var invalidData = ML.Data.LoadFromEnumerable(wrongCollection); 102var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 105ML.Data.SaveAsText(view, fs, headerRow: true, keepHidden: true); 119var dataView = ML.Data.LoadFromEnumerable(data); 224var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\CategoricalTests.cs (10)
70var dataView = ML.Data.LoadFromEnumerable(data); 91ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 108var dataView = mlContext.Data.LoadFromEnumerable(data); 131var dataView = mlContext.Data.LoadFromEnumerable(data); 157var data = ML.Data.LoadFromTextFile(dataPath, new[] { 163var invalidData = ML.Data.LoadFromEnumerable(wrongCollection); 174var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 177ML.Data.SaveAsText(view, fs, headerRow: true, keepHidden: true); 192var dataView = ML.Data.LoadFromEnumerable(data); 318var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\CharTokenizeTests.cs (3)
41var dataView = ML.Data.LoadFromEnumerable(data); 43var invalidDataView = ML.Data.LoadFromEnumerable(invalidData); 61var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\ConcatTests.cs (2)
70data = ML.Data.TakeRows(data, 10); 122data = ML.Data.TakeRows(data, 10);
Transformers\ConvertTests.cs (9)
129var dataView = ML.Data.LoadFromEnumerable(data); 168var allTypesDataView = ML.Data.LoadFromEnumerable(allTypesData); 248var expectedConvertedValues = ML.Data.LoadFromEnumerable(allTypesDataConverted); 253var allInputTypesDataView = ML.Data.LoadFromEnumerable(allInputTypesData); 266var expectedValuesDataView = ML.Data.LoadFromEnumerable(expectedValuesData); 284var dataView = mlContext.Data.LoadFromEnumerable(data); 319var dataView = ML.Data.LoadFromEnumerable(data); 345var dataView = ML.Data.LoadFromEnumerable(data); 388var dataView = ML.Data.LoadFromEnumerable(dataArray);
Transformers\CopyColumnEstimatorTests.cs (7)
49var dataView = env.Data.LoadFromEnumerable(data); 61var dataView = env.Data.LoadFromEnumerable(data); 79var dataView = env.Data.LoadFromEnumerable(data); 80var xyDataView = env.Data.LoadFromEnumerable(xydata); 98var dataView = env.Data.LoadFromEnumerable(data); 116var dataView = env.Data.LoadFromEnumerable(data); 135var dataView = env.Data.LoadFromEnumerable(data);
Transformers\CountTargetEncodingTests.cs (5)
26var data = ML.Data.LoadFromTextFile(dataPath, new[] { 42var data = ML.Data.LoadFromTextFile(dataPath, new[] { new TextLoader.Column("Label", DataKind.Single, 0), 57var data = ML.Data.LoadFromTextFile(dataPath, new[] { 77var data = ML.Data.LoadFromTextFile(dataPath, new[] { 162var data = ML.Data.LoadFromTextFile(dataPath, new[] {
Transformers\CustomMappingTests.cs (9)
56var loader = ML.Data.CreateTextLoader(new[] { 79var inputs = ML.Data.CreateEnumerable<MyInput>(transformedData, true); 80var outputs = ML.Data.CreateEnumerable<MyOutput>(transformedData, true); 92var loader = ML.Data.CreateTextLoader(new[] { 170var loader = ML.Data.CreateTextLoader(new[] { 195var loader = ML.Data.CreateTextLoader(new[] { 201var filteredData = ML.Data.FilterByCustomPredicate<MyInput>(data, input => input.Float1 % 2 == 0); 219var data = ML.Data.LoadFromEnumerable(new[] 232var filteredData = ML.Data.FilterByStatefulCustomPredicate<MyFilterInput, MyFilterState>(data,
Transformers\FeatureSelectionTests.cs (12)
31var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 36var invalidData = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 50var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 65var data = ML.Data.LoadFromTextFile(dataPath, new[] { 87var savedData = ML.Data.TakeRows(trans.Transform(data), 4); 107var data = ML.Data.LoadFromTextFile(dataPath, new[] { 129var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 148var dataView = ML.Data.LoadFromTextFile(dataPath, new[] { 170var data = ML.Data.LoadFromTextFile(dataPath, new[] { 189var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 208var dataView = ML.Data.LoadFromTextFile(dataPath, new[] { 230var dataView = ML.Data.LoadFromTextFile(dataPath, new[] {
Transformers\GroupUngroup.cs (4)
49var dataView = ML.Data.LoadFromEnumerable(data); 52var grouped = ML.Data.CreateEnumerable<UngroupExample>(groupTransform, false).ToList(); 86var dataView = ML.Data.LoadFromEnumerable(data); 89var ungrouped = ML.Data.CreateEnumerable<GroupExample>(ungroupTransform, false).ToList();
Transformers\HashTests.cs (6)
50var dataView = ML.Data.LoadFromEnumerable(data); 72var dataView = ML.Data.LoadFromEnumerable(data); 112var dataView = ML.Data.LoadFromEnumerable(data); 335IDataView data = ML.Data.LoadFromEnumerable(samples); 357var dataView = ML.Data.LoadFromTextFile(dataPath, new[] 381var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\KeyToBinaryVectorEstimatorTest.cs (4)
47var dataView = ML.Data.LoadFromEnumerable(data); 63var data = ML.Data.LoadFromTextFile(dataPath, new[] { 91var dataView = ML.Data.LoadFromEnumerable(data); 147var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\KeyToValueTests.cs (1)
68var data = ML.Data.LoadFromTextFile(dataPath, new[] {
Transformers\KeyToVectorEstimatorTests.cs (5)
54var dataView = ML.Data.LoadFromEnumerable(data); 73var data = ML.Data.LoadFromTextFile(dataPath, new[] { 101var dataView = ML.Data.LoadFromEnumerable(data); 206var dataView = ML.Data.LoadFromEnumerable(data); 254IDataView dataview = mlContext.Data.LoadFromEnumerable(GetData());
Transformers\NAIndicatorTests.cs (6)
46var dataView = ML.Data.LoadFromEnumerable(data); 74var dataView = ML.Data.LoadFromEnumerable(data); 95var data = ML.Data.LoadFromTextFile(dataPath, new[] { 103var invalidData = ML.Data.LoadFromEnumerable(wrongCollection); 117var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 137var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\NAReplaceTests.cs (8)
66var dataView = ML.Data.LoadFromEnumerable(data); 87var expectedOutputDataview = ML.Data.LoadFromEnumerable(expectedOutput); 111var dataView = ML.Data.LoadFromEnumerable(data); 125var data = ML.Data.LoadFromTextFile(dataPath, new[] { 133var invalidData = ML.Data.LoadFromEnumerable(wrongCollection); 143var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 146ML.Data.SaveAsText(view, fs, headerRow: true, keepHidden: true); 169var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\NormalizerTests.cs (20)
656var data = ML.Data.LoadFromTextFile(dataSource, new[] { 661var invalidData = ML.Data.LoadFromTextFile(dataSource, new[] { 675var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 690var data = ML.Data.LoadFromTextFile(dataSource, new[] { 695var invalidData = ML.Data.LoadFromTextFile(dataSource, new[] { 709var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 732var dataView = ML.Data.LoadFromTextFile(dataSource, new[] { 754var data = ML.Data.LoadFromTextFile(dataSource, new[] { 759var invalidData = ML.Data.LoadFromTextFile(dataSource, new[] { 772var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 793var dataView = ML.Data.LoadFromTextFile(dataSource, new[] { 814var data = ML.Data.LoadFromTextFile(dataSource, new[] { 819var invalidData = ML.Data.LoadFromTextFile(dataSource, new[] { 832var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 853var dataView = ML.Data.LoadFromTextFile(dataSource, new[] { 905var data = ML.Data.LoadFromEnumerable(samples); 930var transformedDataArray = ML.Data.CreateEnumerable<DataPointOne>(noCdfData, false).ToImmutableArray(); 946var data = ML.Data.LoadFromEnumerable(samples); 974var transformedDataArray = ML.Data.CreateEnumerable<DataPointVec>(noCdfData, false).ToImmutableArray(); 1054var data = ML.Data.LoadFromEnumerable(samples);
Transformers\PcaTests.cs (5)
29var data = ML.Data.LoadFromTextFile(_dataSource, new[] { 35var invalidData = ML.Data.LoadFromTextFile(_dataSource, new[] { 53var data = ML.Data.LoadFromTextFile(_dataSource, new[] { 60var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 64ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true);
Transformers\RffTests.cs (7)
50var invalidData = ML.Data.LoadFromEnumerable(new[] { new TestClassInvalidSchema { A = 1 }, new TestClassInvalidSchema { A = 1 } }); 51var validFitInvalidData = ML.Data.LoadFromEnumerable(new[] { new TestClassBiggerSize { A = new float[200] }, new TestClassBiggerSize { A = new float[200] } }); 52var dataView = ML.Data.LoadFromEnumerable(data); 67var data = ML.Data.LoadFromTextFile(dataPath, new[] { 77var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 79ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 98var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\SelectColumnsTests.cs (14)
48var dataView = ML.Data.LoadFromEnumerable(data); 67var dataView = ML.Data.LoadFromEnumerable(data); 88var dataView = ML.Data.LoadFromEnumerable(data); 107var dataView = ML.Data.LoadFromEnumerable(data); 108var invalidDataView = ML.Data.LoadFromEnumerable(invalidData); 123var dataView = ML.Data.LoadFromEnumerable(data); 132var dataView = ML.Data.LoadFromEnumerable(data); 155var dataView = ML.Data.LoadFromEnumerable(data); 178var dataView = ML.Data.LoadFromEnumerable(data); 197var dataView = ML.Data.LoadFromEnumerable(data); 219var dataView = ML.Data.LoadFromEnumerable(data); 247var dataView = ML.Data.LoadFromEnumerable(data); 275var dataView = ML.Data.LoadFromEnumerable(data); 303var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\TextFeaturizerTests.cs (39)
49var dataView = ML.Data.LoadFromEnumerable(data); 67var dataView = ML.Data.LoadFromEnumerable(data); 96var dataView = ML.Data.LoadFromEnumerable(data); 138var dataView = ML.Data.LoadFromEnumerable(data); 180var dataView = ML.Data.LoadFromEnumerable(data); 209var dataView = ML.Data.LoadFromEnumerable(data); 240var dataView = ML.Data.LoadFromEnumerable(data); 301var dataView = ML.Data.LoadFromEnumerable(data); 340var dataView = ML.Data.LoadFromEnumerable(data); 378var dataView = ML.Data.LoadFromEnumerable(data); 415var dataView = ML.Data.LoadFromEnumerable(data); 426var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 431var invalidData = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 444var savedData = ML.Data.TakeRows(feat.Fit(data).Transform(data), 4); 459var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 464var invalidData = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 475var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 479ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 489var data = ML.Data.LoadFromTextFile(dataPath, new[] { 495var outdata = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 526var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 531var invalidData = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 544var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 547ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 589var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 594var invalidData = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 605var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 609ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 619var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 624var invalidData = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 640var savedData = ML.Data.TakeRows(est.Fit(data).Transform(data), 4); 644ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 656var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 673var data = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 678var invalidData = ML.Data.LoadFromTextFile(sentimentDataPath, new[] { 699var savedData = ML.Data.TakeRows(transformedData, 4); 761var testData = ML.Data.CreateEnumerable<SentimentData>( 762ML.Data.LoadFromTextFile(GetDataPath(TestDatasets.Sentiment.testFilename), 777var dataView = ML.Data.LoadFromTextFile(dataPath, new[] {
Transformers\TextNormalizer.cs (6)
42var dataView = ML.Data.LoadFromEnumerable(data); 47var invalidDataView = ML.Data.LoadFromEnumerable(invalidData); 51dataView = ML.Data.LoadFromTextFile(dataPath, new[] { 63var savedData = ML.Data.TakeRows(pipeVariations.Fit(dataView).Transform(dataView), 5); 65ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 81var dataView = ML.Data.LoadFromEnumerable(data);
Transformers\ValueMappingTests.cs (27)
53var dataView = ML.Data.LoadFromEnumerable(data); 91var dataView = ML.Data.LoadFromEnumerable(data); 137var dataView = ML.Data.LoadFromEnumerable(data); 172var dataView = ML.Data.LoadFromEnumerable(data); 227var dataView = ML.Data.LoadFromEnumerable(data); 234var mapView = ML.Data.LoadFromEnumerable(map); 261var dataView = ML.Data.LoadFromEnumerable(data); 305var dataView = ML.Data.LoadFromEnumerable(data); 343var dataView = ML.Data.LoadFromEnumerable(data); 362var dataView = ML.Data.LoadFromEnumerable(data); 394var dataView = ML.Data.LoadFromEnumerable(data); 427var dataView = ML.Data.LoadFromEnumerable(data); 469var dataView = ML.Data.LoadFromEnumerable(data); 509var dataView = ML.Data.LoadFromEnumerable(data); 550var dataView = ML.Data.LoadFromEnumerable(data); 590var dataView = ML.Data.LoadFromEnumerable(data); 592var badDataView = ML.Data.LoadFromEnumerable(badData); 609var dataView = ML.Data.LoadFromEnumerable(data); 611var badDataView = ML.Data.LoadFromEnumerable(badData); 628var dataView = ML.Data.LoadFromEnumerable(data); 631var badDataView = ML.Data.LoadFromEnumerable(badData); 685var dataView = ML.Data.LoadFromEnumerable(data); 715var dataView = ML.Data.LoadFromEnumerable(data); 732var dataView = ML.Data.LoadFromEnumerable(data); 763var data = ML.Data.LoadFromEnumerable(rawData); 775var lookupIdvMap = ML.Data.LoadFromEnumerable(lookupData); 784var features = ML.Data.CreateEnumerable<TransformedData>(transformedData, reuseRowObject: false).ToList();
Transformers\WordBagTransformerTests.cs (4)
38var dataview = mlContext.Data.LoadFromEnumerable(samples); 67var dataview = mlContext.Data.LoadFromEnumerable(samples); 105var dataviewDefault = mlContext.Data.LoadFromEnumerable(samplesDefault); 106var dataviewNonDefault = mlContext.Data.LoadFromEnumerable(samplesNonDefault);
Transformers\WordEmbeddingsTests.cs (4)
51var savedData = ML.Data.TakeRows(pipe.Fit(words).Transform(words), 4); 55ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true); 94var savedData = ML.Data.TakeRows(pipe.Fit(words).Transform(words), 10); 98ML.Data.SaveAsText(savedData, fs, headerRow: true, keepHidden: true);
Transformers\WordTokenizeTests.cs (4)
55var dataView = ML.Data.LoadFromEnumerable(data); 57var invalidDataView = ML.Data.LoadFromEnumerable(invalidData); 69var nativeResult = ML.Data.CreateEnumerable<NativeResult>(result, false).First(); 99var dataView = ML.Data.LoadFromEnumerable(data);
Microsoft.ML.TimeSeries.Tests (56)
TimeSeriesDirectApi.cs (33)
113var dataView = env.Data.LoadFromEnumerable(data); 132var enumerator = env.Data.CreateEnumerable<Prediction>(output, true).GetEnumerator(); 158var dataView = env.Data.LoadFromEnumerable(data); 182var enumerator = env.Data.CreateEnumerable<Prediction>(output, true).GetEnumerator(); 216var dataView = ml.Data.LoadFromEnumerable(data); 292var dataView = ml.Data.LoadFromEnumerable(data); 360var dataView = env.Data.LoadFromEnumerable(data); 388var enumerator = env.Data.CreateEnumerable<ForecastPrediction>(output, true).GetEnumerator(); 425var dataView = ml.Data.LoadFromEnumerable(data); 539dataView = ml.Data.LoadFromTextFile(dataPath, new[] { 558dataView = ml.Data.LoadFromEnumerable(data); 569var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>(transformedData, reuseRowObject: false); 597dataView = ml.Data.LoadFromTextFile<TimeSeriesDataDouble>(dataPath, hasHeader: true); 598data = ml.Data.CreateEnumerable<TimeSeriesDataDouble>(dataView, reuseRowObject: false).ToList(); 615dataView = ml.Data.LoadFromEnumerable(data); 627var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>( 685dataView = ml.Data.LoadFromTextFile<TimeSeriesDataDouble>(dataPath, hasHeader: true); 686data = ml.Data.CreateEnumerable<TimeSeriesDataDouble>(dataView, reuseRowObject: false).ToList(); 706var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>( 732dataView = ml.Data.LoadFromTextFile<TimeSeriesDataDouble>(dataPath, hasHeader: true); 733data = ml.Data.CreateEnumerable<TimeSeriesDataDouble>(dataView, reuseRowObject: false).ToList(); 753var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>( 787dataView = ml.Data.LoadFromTextFile<TimeSeriesDataDouble>(dataPath, hasHeader: true); 788data = ml.Data.CreateEnumerable<TimeSeriesDataDouble>(dataView, reuseRowObject: false).ToList(); 808var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>( 846dataView = ml.Data.LoadFromTextFile<TimeSeriesDataDouble>(dataPath, hasHeader: true); 847data = ml.Data.CreateEnumerable<TimeSeriesDataDouble>(dataView, reuseRowObject: false).ToList(); 867var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>( 904dataView = ml.Data.LoadFromTextFile<TimeSeriesDataDouble>(dataPath, hasHeader: true); 905data = ml.Data.CreateEnumerable<TimeSeriesDataDouble>(dataView, reuseRowObject: false).ToList(); 915dataView = ml.Data.LoadFromEnumerable<TimeSeriesDataDouble>(data); 935var predictionColumn = ml.Data.CreateEnumerable<SrCnnAnomalyDetection>( 1076var dataView = mlContext.Data.LoadFromEnumerable(input);
TimeSeriesEstimatorTests.cs (15)
54var dataView = ML.Data.LoadFromEnumerable(data); 69var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 70var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData); 88var dataView = ml.Data.LoadFromEnumerable(data); 105var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 106var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData); 124var dataView = ML.Data.LoadFromEnumerable(data); 139var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 140var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData); 155var dataView = ML.Data.LoadFromEnumerable(data); 166var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 167var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData); 182var dataView = ML.Data.LoadFromEnumerable(data); 193var invalidDataWrongNames = ML.Data.LoadFromEnumerable(xyData); 194var invalidDataWrongTypes = ML.Data.LoadFromEnumerable(stringData);
TimeSeriesSimpleApiTests.cs (8)
44var dataView = env.Data.LoadFromEnumerable(data); 60var enumerator = env.Data.CreateEnumerable<ChangePointPrediction>(output, true).GetEnumerator(); 86var dataView = env.Data.LoadFromEnumerable(data); 103var enumerator = env.Data.CreateEnumerable<ChangePointPrediction>(output, true).GetEnumerator(); 129var dataView = env.Data.LoadFromEnumerable(data); 144var enumerator = env.Data.CreateEnumerable<SpikePrediction>(output, true).GetEnumerator(); 181var dataView = env.Data.LoadFromEnumerable(data); 196var enumerator = env.Data.CreateEnumerable<SpikePrediction>(output, true).GetEnumerator();
Microsoft.ML.TorchSharp.Tests (15)
NerTests.cs (6)
36var labels = ML.Data.LoadFromEnumerable( 46var dataView = ML.Data.LoadFromEnumerable( 112var labels = ML.Data.LoadFromEnumerable( 125var dataView = ML.Data.LoadFromEnumerable( 195var labels = ML.Data.LoadFromTextFile(labelFilePath, new TextLoader.Column[] 217var trainTest = ML.Data.TrainTestSplit(dataView);
QATests.cs (1)
32var dataView = ML.Data.LoadFromEnumerable(
TextClassificationTests.cs (8)
54var dataView = ML.Data.LoadFromEnumerable( 117var dataNoLabel = ML.Data.LoadFromEnumerable( 175var trainTestSplit = mlContext.Data.TrainTestSplit(df, testFraction: 0.2); 191var dataView = ML.Data.LoadFromEnumerable( 264var dataView = ML.Data.LoadFromEnumerable( 347var dataView = ML.Data.LoadFromEnumerable( 430dataView = ML.Data.FilterRowsByMissingValues(dataView, "relevance"); 432var dataSplit = ML.Data.TrainTestSplit(dataView, testFraction: 0.2);