322 references to Append
Microsoft.ML.AutoML (4)
Experiment\SuggestedPipeline.cs (3)
123pipeline = pipeline.Append(transform.Estimator); 141pipeline = pipeline.Append(learner); 148pipeline = pipeline.Append(transform.Estimator);
Experiment\SuggestedPipelineRunDetails\SuggestedPipelineRunDetailUtil.cs (1)
15return preFeaturizer.Append(estimator);
Microsoft.ML.Core.Tests (1)
UnitTests\TestEntryPoints.cs (1)
1375.Append(mlContext.BinaryClassification.Trainers.AveragedPerceptron());
Microsoft.ML.Fairlearn.Tests (1)
GridSearchTest.cs (1)
96.Append(context.Transforms.Concatenate("Features", "sensitiveFeature_encode", "score_feature"))
Microsoft.ML.IntegrationTests (38)
Datasets\Iris.cs (1)
56.Append(mlContext.Transforms.Conversion.MapValueToKey("GroupId"));
Datasets\TrivialMatrixFactorization.cs (1)
31.Append(mlContext.Transforms.Conversion.MapValueToKey("MatrixRowIndex"));
DataTransformation.cs (2)
176.Append(mlContext.Transforms.NormalizeMinMax("Features")); 203.Append(mlContext.Transforms.Conversion.Hash(new[] {
Evaluation.cs (3)
152.Append(mlContext.Transforms.Conversion.MapValueToKey("Label")) 177.Append(mlContext.Ranking.Trainers.FastTree(new FastTreeRankingTrainer.Options { NumberOfThreads = 1 })); 271.Append(mlContext.Regression.Trainers.FastForest(new FastForestRegressionTrainer.Options { NumberOfThreads = 1 }));
Explainability.cs (8)
39.Append(mlContext.Regression.Trainers.FastTree()); 97.Append(mlContext.Regression.Trainers.Sdca()); 121.Append(mlContext.Regression.Trainers.FastTree()); 148.Append(mlContext.Regression.Trainers.FastForest()); 175.Append(mlContext.Regression.Trainers.Sdca()); 212.Append(mlContext.Regression.Trainers.FastTree()); 249.Append(mlContext.Regression.Trainers.FastForest()); 287.Append(mlContext.Regression.Trainers.Gam(numberOfIterations: 2));
IntrospectiveTraining.cs (9)
39.Append(mlContext.Regression.Trainers.FastForest( 144.Append(mlContext.Regression.Trainers.Gam( 185.Append(mlContext.Transforms.Text.LatentDirichletAllocation("Features", "SentimentBag", 265.Append(mlContext.Transforms.NormalizeMinMax("Features")); 293.Append(mlContext.Regression.Trainers.FastForest(numberOfLeaves: 5, numberOfTrees: 3)); 338.Append(mlContext.Transforms.Concatenate("CategoricalFeatures", Adult.CategoricalFeatures)) 395.Append(StepOne(mlContext)) 420.Append(mlContext.Clustering.Trainers.KMeans( 433.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy(
ModelFiles.cs (2)
49.Append(mlContext.Regression.Trainers.FastTree( 96.Append(mlContext.Regression.Trainers.FastTree(
ONNX.cs (3)
41.Append(mlContext.Transforms.NormalizeMinMax("Features")) 91.Append(mlContext.Transforms.NormalizeMinMax("Features")) 143.Append(mlContext.Transforms.NormalizeMinMax("Features"))
SchemaDefinitionTests.cs (3)
37.Append(_ml.Transforms.Concatenate("Features", "Cat", "NumericFeatures")); 41.Append(_ml.Transforms.Concatenate("Features", "Cat", "NumericFeatures")); 67.Append(_ml.Transforms.Categorical.OneHotEncoding("Workclass"))
Training.cs (3)
267.Append(mlContext.Transforms.Conversion.MapValueToKey("Label")) 318.Append(mlContext.Transforms.NormalizeMinMax("Features")) 362.Append(mlContext.Transforms.NormalizeMinMax("Features"))
Validation.cs (3)
42.Append(mlContext.Regression.Trainers.Ols()); 68var dataProcessPipeline = mlContext.Transforms.Concatenate("Features", new[] { "FeatureVectorA", "FeatureVectorB" }).Append( 155.Append(mlContext.Regression.Trainers.OnlineGradientDescent());
Microsoft.ML.OnnxTransformerTest (7)
DnnImageFeaturizerTest.cs (3)
110.Append(ML.Transforms.ResizeImages("data_0", imageHeight, imageWidth)) 222.Append(ML.Transforms.LoadImages("ImagePath_featurized", imageFolder, "ImagePath")) 231.Append(ML.Transforms.Conversion.MapKeyToValue("PredictedLabel", "PredictedLabel"));
OnnxTransformTests.cs (4)
255.Append(ML.Transforms.ResizeImages("data_0", imageHeight, imageWidth)) 306.Append(ML.Transforms.ResizeImages("data_0", imageHeight, imageWidth)) 644.Append(ML.Transforms.ApplyOnnxModel("softmaxout_1", "data_0", modelFile, gpuDeviceId: _gpuDeviceId, fallbackToCpu: _fallbackToCpu)); // Map column "data_0" to column "softmaxout_1" 1135.Append(ML.Transforms.ResizeImages("data_0", imageHeight, imageWidth))
Microsoft.ML.PerformanceTests (8)
FeaturizeTextBench.cs (1)
77pipeline = pipeline.Append(featurizer);
ImageClassificationBench.cs (2)
62.Append(_mlContext.Transforms.LoadRawImageBytes("Image", 92.Append(_mlContext.Transforms.Conversion.MapKeyToValue(
KMeansAndLogisticRegressionBench.cs (1)
37.Append(ml.Transforms.NormalizeMinMax("NumFeatures"))
PredictionEngineBench.cs (2)
58.Append(env.Transforms.Conversion.MapValueToKey("Label")) 94.Append(mlContext.BinaryClassification.Trainers.SdcaNonCalibrated(
StochasticDualCoordinateAscentClassifierBench.cs (2)
79.Append(_mlContext.Transforms.Conversion.MapValueToKey("Label")) 114.Append(_mlContext.Transforms.Conversion.MapValueToKey("Label"))
Microsoft.ML.Predictor.Tests (2)
TestIniModels.cs (2)
531.Append(mlContext.Regression.Trainers.Gam()); 570.Append(mlContext.BinaryClassification.Trainers.Gam());
Microsoft.ML.Samples (61)
Dynamic\ModelOperations\OnnxConversion.cs (1)
51.Append(mlContext.Transforms.Categorical.OneHotEncoding("workclass"))
Dynamic\NgramExtraction.cs (2)
53.Append(ngramOnePipeline); 56.Append(ngramTwpPipeline);
Dynamic\TensorFlow\TextClassification.cs (1)
103.Append(mlContext.Transforms.Conversion.MapValue(
Dynamic\Trainers\BinaryClassification\PermutationFeatureImportance.cs (1)
29.Append(mlContext.Transforms.NormalizeMinMax("Features"))
Dynamic\Trainers\BinaryClassification\PermutationFeatureImportanceLoadFromDisk.cs (1)
25.Append(mlContext.Transforms.NormalizeMinMax("Features"))
Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (2)
52.Append(mlContext.Transforms.LoadRawImageBytes("Image", 68.Append(mlContext.Transforms.Conversion.MapKeyToValue(
Dynamic\Trainers\MulticlassClassification\ImageClassification\LearningRateSchedulingCifarResnetTransferLearning.cs (3)
56.Append(mlContext.Transforms.LoadRawImageBytes("Image", 72.Append(mlContext.Transforms.LoadRawImageBytes("Image", 104.Append(mlContext.Transforms.Conversion.MapKeyToValue(
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (2)
51.Append(mlContext.Transforms.LoadRawImageBytes("Image", 93.Append(mlContext.MulticlassClassification.Trainers.
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (2)
51.Append(mlContext.Transforms.LoadRawImageBytes("Image", 84.Append(mlContext.Transforms.Conversion.MapKeyToValue(
Dynamic\Trainers\MulticlassClassification\LbfgsMaximumEntropy.cs (1)
32.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\LbfgsMaximumEntropyWithOptions.cs (1)
40.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\LightGbm.cs (1)
35.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\LightGbmWithOptions.cs (1)
45.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\LogLossPerClass.cs (1)
32.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\NaiveBayes.cs (1)
38.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\OneVersusAll.cs (1)
32.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\PairwiseCoupling.cs (1)
32.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportance.cs (1)
30.Append(mlContext.Transforms.Conversion.MapValueToKey("Label"))
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportanceLoadFromDisk.cs (1)
33.Append(mlContext.Transforms.Conversion.MapValueToKey("Label"))
Dynamic\Trainers\MulticlassClassification\SdcaMaximumEntropy.cs (1)
40.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\SdcaMaximumEntropyWithOptions.cs (1)
49.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\SdcaNonCalibrated.cs (1)
40.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\MulticlassClassification\SdcaNonCalibratedWithOptions.cs (1)
49.Append(mlContext.MulticlassClassification.Trainers
Dynamic\Trainers\Ranking\PermutationFeatureImportance.cs (1)
29.Append(mlContext.Transforms.Conversion.MapValueToKey("Label"))
Dynamic\Trainers\Ranking\PermutationFeatureImportanceLoadFromDisk.cs (1)
31.Append(mlContext.Transforms.Conversion.MapValueToKey("Label"))
Dynamic\Trainers\Regression\LightGbmAdvanced.cs (1)
41.Append(mlContext.Regression.Trainers.LightGbm(
Dynamic\Trainers\Regression\LightGbmWithOptionsAdvanced.cs (1)
42.Append(mlContext.Regression.Trainers.LightGbm(
Dynamic\Trainers\Regression\PermutationFeatureImportance.cs (1)
31.Append(mlContext.Transforms.NormalizeMinMax("Features"))
Dynamic\Trainers\Regression\PermutationFeatureImportanceLoadFromDisk.cs (1)
33.Append(mlContext.Transforms.NormalizeMinMax("Features"))
Dynamic\Transforms\ApplyONNXModelWithInMemoryImages.cs (1)
46.Append(mlContext.Transforms.ApplyOnnxModel("softmaxout_1",
Dynamic\Transforms\CalculateFeatureContribution.cs (1)
27.Append(mlContext.Transforms.NormalizeMeanVariance("Features"));
Dynamic\Transforms\CalculateFeatureContributionCalibrated.cs (1)
27.Append(mlContext.Transforms.NormalizeMeanVariance("Features"));
Dynamic\Transforms\Concatenate.cs (1)
51.Append(mlContext.Transforms.Concatenate("Features", new[]
Dynamic\Transforms\Conversion\Hash.cs (1)
45.Append(mlContext.Transforms.Conversion.Hash("AgeHashed", "Age",
Dynamic\Transforms\Conversion\KeyToValueToKey.cs (2)
31"TokenizedText", nameof(DataPoint.Review)).Append(mlContext 42"TokenizedText", nameof(DataPoint.Review)).Append(mlContext
Dynamic\Transforms\Conversion\MapKeyToValueMultiColumn.cs (1)
34.Append(mlContext.MulticlassClassification.Trainers.
Dynamic\Transforms\Conversion\MapKeyToVector.cs (1)
44.Append(mlContext.Transforms.Concatenate("Parts", "PartA", "PartB"))
Dynamic\Transforms\Conversion\MapValue.cs (1)
57"TimeframeCategory", timeframeMap, "Timeframe").Append(mlContext.
Dynamic\Transforms\Expression.cs (1)
34.Append(mlContext.Transforms.Expression("Expr2", "(b,s,i)=>b ? len(s) : i",
Dynamic\Transforms\FeatureSelection\SelectFeaturesBasedOnCount.cs (1)
40.Append(mlContext.Transforms.FeatureSelection
Dynamic\Transforms\ImageAnalytics\ConvertToGrayScale.cs (1)
47.Append(mlContext.Transforms.ConvertToGrayscale("Grayscale",
Dynamic\Transforms\ImageAnalytics\ConvertToImage.cs (1)
34.Append(mlContext.Transforms.ExtractPixels("Pixels", "Image"));
Dynamic\Transforms\ImageAnalytics\DnnFeaturizeImage.cs (1)
49.Append(mlContext.Transforms.ResizeImages("ImageObject", imageWidth:
Dynamic\Transforms\ImageAnalytics\ExtractPixels.cs (1)
49.Append(mlContext.Transforms.ResizeImages("ImageObjectResized",
Dynamic\Transforms\ImageAnalytics\ResizeImages.cs (1)
46.Append(mlContext.Transforms.ResizeImages("ImageObjectResized",
Dynamic\Transforms\Text\ApplyCustomWordEmbedding.cs (1)
48.Append(mlContext.Transforms.Text.TokenizeIntoWords("Tokens",
Dynamic\Transforms\Text\ApplyWordEmbedding.cs (1)
37.Append(mlContext.Transforms.Text.TokenizeIntoWords("Tokens",
Dynamic\Transforms\Text\LatentDirichletAllocation.cs (1)
42.Append(mlContext.Transforms.Text.TokenizeIntoWords("Tokens",
Dynamic\Transforms\Text\ProduceHashedNgrams.cs (1)
47.Append(mlContext.Transforms.Conversion.MapValueToKey("Tokens"))
Dynamic\Transforms\Text\ProduceNgrams.cs (1)
56.Append(mlContext.Transforms.Conversion.MapValueToKey("Tokens"))
Dynamic\Transforms\Text\RemoveDefaultStopWords.cs (1)
32.Append(mlContext.Transforms.Text.RemoveDefaultStopWords(
Dynamic\Transforms\Text\RemoveStopWords.cs (1)
31.Append(mlContext.Transforms.Text.RemoveStopWords(
Dynamic\Transforms\Text\TokenizeIntoCharactersAsKeys.cs (1)
31.Append(mlContext.Transforms.Conversion.MapKeyToValue(
Dynamic\WithOnFitDelegate.cs (1)
48.Append(mlContext.BinaryClassification.Trainers
Microsoft.ML.Samples.GPU (10)
docs\samples\Microsoft.ML.Samples\Dynamic\TensorFlow\TextClassification.cs (1)
103.Append(mlContext.Transforms.Conversion.MapValue(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (2)
52.Append(mlContext.Transforms.LoadRawImageBytes("Image", 68.Append(mlContext.Transforms.Conversion.MapKeyToValue(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\LearningRateSchedulingCifarResnetTransferLearning.cs (3)
56.Append(mlContext.Transforms.LoadRawImageBytes("Image", 72.Append(mlContext.Transforms.LoadRawImageBytes("Image", 104.Append(mlContext.Transforms.Conversion.MapKeyToValue(
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (2)
51.Append(mlContext.Transforms.LoadRawImageBytes("Image", 93.Append(mlContext.MulticlassClassification.Trainers.
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (2)
51.Append(mlContext.Transforms.LoadRawImageBytes("Image", 84.Append(mlContext.Transforms.Conversion.MapKeyToValue(
Microsoft.ML.SamplesUtils (1)
SamplesDatasetUtils.cs (1)
93.Append(mlContext.Transforms.Categorical.OneHotEncoding("workclass"))
Microsoft.ML.TensorFlow.Tests (20)
TensorFlowEstimatorTests.cs (4)
163.Append(ML.Transforms.ResizeImages("Input", imageHeight, imageWidth)) 206.Append(ML.Transforms.ResizeImages("Input", imageHeight, imageWidth)) 220.Append(ML.Transforms.ResizeImages("Input", imageHeight, imageWidth)) 256.Append(ML.Transforms.ResizeImages("Input", imageHeight, imageWidth))
TensorflowTests.cs (16)
149.Append(new ImageResizingEstimator(_mlContext, "ImageCropped", imageHeight, imageWidth, "ImageReal")) 669.Append(_mlContext.Model.LoadTensorFlowModel("mnist_model/frozen_saved_model.pb").ScoreTensorFlowModel(new[] { "Softmax", "dense/Relu" }, new[] { "Placeholder", "reshape_input" })) 893.Append(_mlContext.Model.LoadTensorFlowModel("mnist_model").ScoreTensorFlowModel(new[] { "Softmax", "dense/Relu" }, new[] { "Placeholder", "reshape_input" })) 1021.Append(new ImageResizingEstimator(_mlContext, "ImageCropped", 1117.Append(_mlContext.Transforms.ExtractPixels("Input", "ResizedImage", interleavePixelColors: true)) 1159.Append(new ImageResizingEstimator(_mlContext, "ImageCropped", imageHeight, imageWidth, "ImageReal")) 1290.Append(_mlContext.Transforms.CopyColumns("Prediction", "Prediction/Softmax")) 1351.Append(_mlContext.Transforms.CopyColumns(new[] { new InputOutputColumnPair("AOut", "Original_A"), new InputOutputColumnPair("BOut", "Joined_Splited_Text") })); 1419.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification("Label", "Image") 1420.Append(_mlContext.Transforms.Conversion.MapKeyToValue(outputColumnName: "PredictedLabel", inputColumnName: "PredictedLabel"))); ; 1522.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification(options) 1523.Append(_mlContext.Transforms.Conversion.MapKeyToValue(outputColumnName: "PredictedLabel", inputColumnName: "PredictedLabel"))); 1680.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification(options)) 1814.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification(options)); 1859.Append(_mlContext.Transforms.LoadRawImageBytes("Image", fullImagesetFolderPath, "ImagePath")) 2063.Append(_mlContext.Transforms.ResizeImages("Input", imageHeight, imageWidth))
Microsoft.ML.Tests (153)
CachingTests.cs (1)
46.Append(ML.Transforms.NormalizeMinMax("Norm1", "F1"))
CalibratedModelParametersTests.cs (1)
134.Append(ML.Transforms.NormalizeMinMax("Features"));
DatabaseLoaderTests.cs (5)
68.Append(mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")) 104.Append(mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth")) 140.Append(mlContext.Transforms.Concatenate("Features", "SepalInfo", "PetalInfo")) 172.Append(mlContext.Transforms.Concatenate("Features", "SepalInfo", "PetalInfo")) 204.Append(mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth"))
FeatureContributionTests.cs (5)
34.Append(ML.Transforms.CalculateFeatureContribution(model, normalize: false)) 202.Append(ML.Transforms.CalculateFeatureContribution(model, numberOfPositiveContributions: 0, numberOfNegativeContributions: 3)) 226.Append(ML.Transforms.CalculateFeatureContribution(model, numberOfPositiveContributions: 0, numberOfNegativeContributions: 3)) 315.Append(ML.Transforms.NormalizeMinMax("Features")); 425.Append(ML.Transforms.Categorical.OneHotEncoding(outputColumnName: vendorIdEncoded, inputColumnName: nameof(TaxiTrip.VendorId)))
ImagesTests.cs (3)
51.Append(new ImageResizingEstimator(env, "ImageReal", 100, 100, "ImageReal")) 75.Append(new ImageResizingEstimator(env, "ImageReal", 100, 100, "ImageReal")) 1022.Append(new ImageResizingEstimator(env, "ImageReal", targetDimension, targetDimension, "ImageReal",
OnnxConversionTest.cs (22)
154Append(mlContext.Clustering.Trainers.KMeans(new Trainers.KMeansTrainer.Options 246Append(mlContext.Transforms.NormalizeMinMax("Features")); 268.Append(new VectorWhiteningEstimator(mlContext, "whitened2", "features", kind: WhiteningKind.PrincipalComponentAnalysis, rank: 5)); 301Append(ML.Transforms.NormalizeMinMax("Features")); 390var pipeline = new TextNormalizingEstimator(mlContext, keepDiacritics: true, columns: new[] { ("NormText", "text") }).Append( 629Append(mlContext.Transforms.NormalizeMinMax("Features")). 793.Append(mlContext.Transforms.ReplaceMissingValues(new MissingValueReplacingEstimator.ColumnOptions("F2"))) 1168.Append(mlContext.Transforms.Conversion.ConvertType("MissingIndicator", outputKind: DataKind.Int32)); 1411Append(mlContext.Transforms.Conversion.MapKeyToValue("Value", "Key")), 1414Append(mlContext.Transforms.Conversion.MapKeyToValue("Value")) 1479.Append(mlContext.Transforms.Conversion.MapValueToKey("Tokens")) 1486.Append(mlContext.Transforms.Text.ProduceNgrams("NGrams", "Tokens", 1497.Append(mlContext.Transforms.Text.ProduceWordBags("Tokens", "Tokens0")) 1542.Append(mlContext.Transforms.Text.RemoveStopWords( 1566.Append(mlContext.Transforms.Text.RemoveDefaultStopWords( 1681.Append(mlContext.Transforms.NormalizeMinMax("Features")) 1857Append(mlContext.Transforms.FeatureSelection.SelectFeaturesBasedOnCount("ScalarOutput", "Scalar", count: 100)), 1861Append(mlContext.Transforms.FeatureSelection.SelectFeaturesBasedOnCount("ScalarOutput", "Scalar", count: 800)), 1864Append(mlContext.Transforms.FeatureSelection.SelectFeaturesBasedOnMutualInformation("ScalarOutput", "Scalar")) 1898var pipeline = mlContext.Transforms.ReplaceMissingValues("Size").Append(mlContext.Transforms.SelectColumns(new[] { "Size", "Shape", "Thickness", "Label" })); 1957Append(mlContext.Transforms.NormalizeMinMax("MyFeatureVector")); 2006.Append(mlContext.Transforms.NormalizeMinMax("MyFeatureVector"))
PermutationFeatureImportanceTests.cs (3)
106var model = ML.Transforms.CopyColumns("Label", "Label").Append(ML.Regression.Trainers.OnlineGradientDescent()).Fit(data); 859.Append(ML.Transforms.NormalizeMinMax("Features")); 939.Append(ML.Transforms.NormalizeMinMax("Features"));
Scenarios\Api\CookbookSamples\CookbookSamplesDynamicApi.cs (10)
106.Append(mlContext.BinaryClassification.Trainers 232.Append(mlContext.Transforms.Conversion.MapValueToKey("Label"), TransformerScope.TrainTest) 353.Append(context.Regression.Trainers.FastTree()); 393.Append(context.Regression.Trainers.Sdca()); 428.Append(context.Regression.Trainers.FastTree()); 464.Append(context.Regression.Trainers.FastTree(labelColumnName: "MedianHomeValue")); 524.Append(mlContext.Transforms.Text.NormalizeText("NormalizedMessage", "Message")) 597.Append(mlContext.Transforms.Categorical.OneHotEncoding("CategoricalBag", "CategoricalFeatures", OneHotEncodingEstimator.OutputKind.Bag)) 646.Append(mlContext.Transforms.Conversion.MapValueToKey("Label"), TransformerScope.TrainTest) 742.Append(mlContext.BinaryClassification.Trainers.FastTree(labelColumnName: "Label"));
Scenarios\Api\Estimators\DecomposableTrainAndPredict.cs (1)
34.Append(new ValueToKeyMappingEstimator(ml, "Label"), TransformerScope.TrainTest)
Scenarios\Api\Estimators\Extensibility.cs (1)
42.Append(new CustomMappingEstimator<IrisData, IrisData>(ml, action, null), TransformerScope.TrainTest)
Scenarios\Api\Estimators\PredictAndMetadata.cs (3)
32.Append(ml.Transforms.Conversion.MapValueToKey("Label"), TransformerScope.TrainTest) 81.Append(mlContext.Transforms.Conversion.MapValueToKey("Label")) 116.Append(mlContext.MulticlassClassification.Trainers.OneVersusAll(singleTrainer));
Scenarios\IrisPlantClassificationTests.cs (1)
33.Append(mlContext.Transforms.NormalizeMinMax("Features"))
Scenarios\IrisPlantClassificationWithStringLabelTests.cs (1)
37.Append(mlContext.Transforms.NormalizeMinMax("Features"))
Scenarios\RegressionTest.cs (1)
28.Append(context.Transforms.Categorical.OneHotEncoding(outputColumnName: "VendorIdEncoded", inputColumnName: "VendorId"))
Scenarios\WordBagTest.cs (2)
33ngramLength: 3, useAllLengths: false, weighting: NgramExtractingEstimator.WeightingCriteria.Tf).Append( 69mlContext.Transforms.Text.ProduceHashedWordBags("Text", "Text", ngramLength: 3, useAllLengths: false).Append(
ScenariosWithDirectInstantiation\IrisPlantClassificationTests.cs (1)
31.Append(mlContext.Transforms.NormalizeMinMax("Features"))
TrainerEstimators\CalibratorEstimators.cs (1)
102pipeline = pipeline.Append(binaryTrainer);
TrainerEstimators\FAFMEstimator.cs (1)
26.Append(mlContext.BinaryClassification.Trainers.FieldAwareFactorizationMachine());
TrainerEstimators\LbfgsTests.cs (6)
23var pipeWithTrainer = pipe.Append(trainer); 37var pipeWithTrainer = pipe.Append(trainer); 63pipe = pipe.Append(ML.BinaryClassification.Trainers.LbfgsLogisticRegression(new LbfgsLogisticRegressionBinaryTrainer.Options { ShowTrainingStatistics = true })); 83pipe = pipe.Append(ML.BinaryClassification.Trainers.LbfgsLogisticRegression( 167var pipeWithTrainer = pipe.Append(trainer); 189var pipeWithTrainer = pipe.Append(trainer);
TrainerEstimators\MetalinearEstimators.cs (4)
32pipeline = pipeline.Append(ova) 49pipeline = pipeline.Append(ML.MulticlassClassification.Trainers.OneVersusAll(sdcaTrainer, useProbabilities: false)) 67pipeline = pipeline.Append(ML.MulticlassClassification.Trainers.PairwiseCoupling(sdcaTrainer)) 98.Append(new ValueToKeyMappingEstimator(Env, "Label"))
TrainerEstimators\SdcaTests.cs (4)
175Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 179Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 278Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy(labelColumnName: "LabelIndex", featureColumnName: "Features", l2Regularization: 0.001f)); 312Append(mlContext.MulticlassClassification.Trainers.SdcaNonCalibrated(labelColumnName: "LabelIndex", featureColumnName: "Features", lossFunction: new HingeLoss(), l2Regularization: 0.001f));
TrainerEstimators\SymSgdClassificationTests.cs (1)
21var pipeWithTrainer = pipe.Append(trainer);
TrainerEstimators\TrainerEstimators.cs (2)
155pipe = pipe.Append(ML.MulticlassClassification.Trainers.NaiveBayes("Label", "Features")); 218var oneHotPipeline = pipeline.Append(ML.Transforms.Categorical.OneHotEncoding("LoggedIn"));
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (13)
331.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 377.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 416.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 455.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 493.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 531.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 569.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 607.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 663.Append(ML.Transforms.FeaturizeByFastForestRegression(options)) 694.Append(ML.Transforms.NormalizeBinning("CopiedFeatures")) 740.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Trees", "Leaves", "Paths")) 751.Append(ML.Transforms.Concatenate("CombinedFeatures", "Features", "Leaves")) 804.Append(ML.Transforms.CustomMapping(actionConvertKeyToFloat, "KeyLabel"))
TrainerEstimators\TreeEstimators.cs (21)
49var pipeWithTrainer = pipe.Append(trainer); 71var pipeWithTrainer = pipe.Append(trainer); 93var pipeWithTrainer = pipe.Append(trainer); 138var pipeWithTrainer = pipe.Append(trainer); 159var pipeWithTrainer = pipe.Append(trainer); 183var pipeWithTrainer = pipe.Append(trainer); 201var pipeWithTrainer = pipe.Append(trainer); 310var pipe = pipeline.Append(trainer) 327var pipe = pipeline.Append(trainer); 350var pipe = pipeline.Append(trainer) 370var pipe = pipeline.Append(trainer) 395var pipe = pipeline.Append(trainer) 414var pipe = pipeline.Append(trainer) 747.Append(mlContext.MulticlassClassification.Trainers 781var pipe = pipeline.Append(trainer) 988var estimator = pipeline.Append(ML.BinaryClassification.Trainers.FastTree( 1006var estimator = pipeline.Append(ML.BinaryClassification.Trainers.FastForest( 1027var estimator = pipeline.Append(context.MulticlassClassification.Trainers.OneVersusAll(context.BinaryClassification.Trainers.FastTree())); 1049var trainer = pipeline.Append(ML.BinaryClassification.Trainers.LightGbm( 1084var trainer = pipeline.Append(context.BinaryClassification.Trainers.LightGbm( 1112var trainer = pipeline.Append(context.MulticlassClassification.Trainers.LightGbm(
Transformers\CategoricalHashTests.cs (1)
90.Append(ML.Transforms.Categorical.OneHotHashEncoding("A", "ScalarString", outputKind: OneHotEncodingEstimator.OutputKind.Indicator))
Transformers\CategoricalTests.cs (2)
110.Append(mlContext.Transforms.Conversion.ConvertType("B", outputKind: DataKind.Single)) 165.Append(ML.Transforms.Categorical.OneHotEncoding("A", "ScalarString", outputKind: OneHotEncodingEstimator.OutputKind.Indicator))
Transformers\ConcatTests.cs (1)
66.Append(ML.Transforms.Concatenate("f2", "float1", "float1"))
Transformers\ConvertTests.cs (1)
341}).Append(ML.Transforms.Conversion.ConvertType(new[] {
Transformers\ExpressionTransformerTests.cs (1)
41Append(ML.Transforms.Expression("Expr2", "(x,y)=>(x+y)/3", "Float", "FloatVector")).
Transformers\FeatureSelectionTests.cs (6)
44.Append(ML.Transforms.FeatureSelection.SelectFeaturesBasedOnMutualInformation("bag_of_words_mi", "bag_of_words", labelColumnName: "label"))); 121.Append(ML.Transforms.FeatureSelection.SelectFeaturesBasedOnCount(columns)); 178.Append(ML.Transforms.FeatureSelection.SelectFeaturesBasedOnMutualInformation(labelColumnName: "Label", slotsInOutput: 2, numberOfBins: 100, 239.Append(ML.Transforms.FeatureSelection.SelectFeaturesBasedOnCount("Features")); 247.Append(ML.Transforms.FeatureSelection.SelectFeaturesBasedOnMutualInformation("Features", labelColumnName: "BadLabel")); 255.Append(ML.Transforms.FeatureSelection.SelectFeaturesBasedOnMutualInformation("Features"));
Transformers\HashTests.cs (1)
384.Append(ML.Transforms.Conversion.Hash(
Transformers\KeyToBinaryVectorEstimatorTest.cs (1)
75.Append(ML.Transforms.Conversion.MapKeyToBinaryVector("VectorString", "B"));
Transformers\KeyToValueTests.cs (1)
79.Append(ML.Transforms.Conversion.MapKeyToValue("VectorString", "B"));
Transformers\KeyToVectorEstimatorTests.cs (2)
84.Append(ML.Transforms.Conversion.MapKeyToVector("VectorString", "B")) 257.Append(mlContext.Transforms.Categorical.OneHotHashEncoding("ProblematicColumn"));
Transformers\NAIndicatorTests.cs (1)
139var newpipe = pipe.Append(ML.Transforms.IndicateMissingValues("NAA", "CatA"));
Transformers\NAReplaceTests.cs (1)
136.Append(ML.Transforms.ReplaceMissingValues("B", "ScalarDouble", replacementMode: MissingValueReplacingEstimator.ReplacementMode.Mean))
Transformers\NormalizerTests.cs (5)
241.Append(context.Transforms.NormalizeBinning( 667.Append(ML.Transforms.NormalizeGlobalContrast("gcnorm", "features")) 702.Append(new VectorWhiteningEstimator(ML, "whitened2", "features", kind: WhiteningKind.PrincipalComponentAnalysis, rank: 5)); 765.Append(ML.Transforms.NormalizeLpNorm("lpNorm2", "features", norm: LpNormNormalizingEstimatorBase.NormFunction.L1, ensureZeroMean: true)); 825.Append(ML.Transforms.NormalizeGlobalContrast("gcnNorm2", "features", ensureZeroMean: false, ensureUnitStandardDeviation: true, scale: 3));
Transformers\SelectColumnsTests.cs (3)
134var chain = est.Append(ColumnSelectingEstimator.KeepColumns(Env, "C", "A")); 157var chain = est.Append(ML.Transforms.SelectColumns(new[] { "B", "A" }, true)); 198var est = new ColumnCopyingEstimator(Env, new[] { ("A", "A"), ("B", "B") }).Append(
Transformers\TextFeaturizerTests.cs (6)
470.Append(new TokenizingByCharactersEstimator(ML, "chars", "text")) 537.Append(ML.Transforms.Text.TokenizeIntoWords("words", "text")) 600Append(new WordHashBagEstimator(ML, "bag_of_wordshash", "text", maximumNumberOfInverts: -1)); 630.Append(new ValueToKeyMappingEstimator(ML, "terms", "text")) 684Append(new LatentDirichletAllocationEstimator(env, "topics", "bag_of_words", 10, maximumNumberOfIterations: 10, 783.Append(ML.BinaryClassification.Trainers.FastTree());
Transformers\TextNormalizer.cs (1)
56var pipeVariations = new TextNormalizingEstimator(ML, columns: new[] { ("NormText", "text") }).Append(
Transformers\ValueMappingTests.cs (3)
107}).Append(valueMappingEstimator); 559Append(ML.Transforms.Conversion.MapKeyToValue("DOutput", "D")); 641.Append(ML.Transforms.Conversion.MapValue("VecB", keyValuePairs, "TokenizeB"));
Transformers\WordEmbeddingsTests.cs (2)
42.Append(ML.Transforms.Text.TokenizeIntoWords("Words", "NormalizedText")) 77.Append(ML.Transforms.Text.TokenizeIntoWords("Words", "NormalizedText"))
Microsoft.ML.TimeSeries.Tests (3)
TimeSeriesDirectApi.cs (3)
228.Append(new SsaChangePointEstimator(ml, new SsaChangePointDetector.Options() 304.Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single)) 450.Append(ml.Transforms.Conversion.ConvertType("Value", "Value", DataKind.Single))
Microsoft.ML.TorchSharp.Tests (4)
ObjectDetectionTests.cs (1)
64.Append(ML.Transforms.Conversion.MapValueToKey("Labels"))
TextClassificationTests.cs (3)
178.Append(mlContext.MulticlassClassification.Trainers.TextClassification(sentence1ColumnName: "Title", sentence2ColumnName: "Description", maxEpochs: 10, batchSize: 8)) 236.Append(ML.MulticlassClassification.Trainers.TextClassification(outputColumnName: "outputColumn")) 321.Append(ML.Transforms.Conversion.MapKeyToValue("outputColumn"));
Microsoft.ML.Transforms (9)
OneHotEncoding.cs (3)
130_transformer = term.Append(toVector).Fit(input); 314_toSomething = toVector.Append(toBinVector); 331return _term.Append(_toSomething).GetOutputSchema(inputSchema);
OneHotHashEncoding.cs (3)
172_transformer = hash.Append(keyToVector).Fit(input); 364_toSomething = toVector.Append(toBinVector); 382return _hash.Append(_toSomething).GetOutputSchema(inputSchema);
Text\WordBagTransform.cs (3)
166estimator = estimator.Append(new TextExpandingEstimator(h, tokenizeColumns[0].InputColumnName, options.FreqSeparator, options.TermSeparator)); 168estimator = estimator.Append(new WordTokenizingEstimator(h, tokenizeColumns)); 169estimator = estimator.Append(NgramExtractorTransform.CreateEstimator(h, extractorArgs, estimator.GetOutputSchema(inputSchema)));