1 write to MulticlassClassification
Microsoft.ML.Data (1)
MLContext.cs (1)
144MulticlassClassification = new MulticlassClassificationCatalog(_env);
229 references to MulticlassClassification
Microsoft.ML.AutoML (27)
API\MulticlassClassificationExperiment.cs (2)
373var metrics = _context.MulticlassClassification.CrossValidate(datasetManager.Dataset, pipeline, fold, metricManager.LabelColumn); 403var metrics = _context.MulticlassClassification.Evaluate(eval, metricManager.LabelColumn, predictedLabelColumnName: metricManager.PredictedColumn);
AutoMLExperiment\IMetricManager.cs (1)
95var metric = context.MulticlassClassification.Evaluate(eval, labelColumnName: LabelColumn, predictedLabelColumnName: PredictedColumn);
Experiment\MetricsAgents\MultiMetricsAgent.cs (1)
71return _mlContext.MulticlassClassification.Evaluate(data, labelColumn);
SweepableEstimator\Estimators\FastForest.cs (1)
23return context.MulticlassClassification.Trainers.OneVersusAll(context.BinaryClassification.Trainers.FastForest(option), labelColumnName: param.LabelColumnName);
SweepableEstimator\Estimators\FastTree.cs (1)
28return context.MulticlassClassification.Trainers.OneVersusAll(context.BinaryClassification.Trainers.FastTree(option), labelColumnName: param.LabelColumnName);
SweepableEstimator\Estimators\Images.cs (1)
54return context.MulticlassClassification.Trainers.ImageClassification(option);
SweepableEstimator\Estimators\Lbfgs.cs (2)
23return context.MulticlassClassification.Trainers.LbfgsMaximumEntropy(option); 78return context.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, param.LabelColumnName);
SweepableEstimator\Estimators\LightGbm.cs (1)
33return context.MulticlassClassification.Trainers.LightGbm(option);
SweepableEstimator\Estimators\NamedEntityRecognitionMulti.cs (1)
17return context.MulticlassClassification.Trainers.NamedEntityRecognition(
SweepableEstimator\Estimators\ObjectDetection.cs (1)
32return context.MulticlassClassification.Trainers.ObjectDetection(option);
SweepableEstimator\Estimators\QuestionAnswering.cs (1)
14return context.MulticlassClassification.Trainers.QuestionAnswer(
SweepableEstimator\Estimators\Sdca.cs (2)
41return context.MulticlassClassification.Trainers.SdcaMaximumEntropy(option); 78return context.MulticlassClassification.Trainers.OneVersusAll(binaryEstimator: binaryTrainer, labelColumnName: param.LabelColumnName);
SweepableEstimator\Estimators\TextClassification.cs (1)
17return context.MulticlassClassification.Trainers.TextClassification(
TrainerExtensions\MultiTrainerExtensions.cs (11)
29return mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, labelColumnName: columnInfo.LabelColumnName); 51return mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, labelColumnName: columnInfo.LabelColumnName); 71return mlContext.MulticlassClassification.Trainers.LightGbm(options); 94return mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, labelColumnName: columnInfo.LabelColumnName); 114return mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy(options); 137return mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, labelColumnName: columnInfo.LabelColumnName); 159return mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, labelColumnName: columnInfo.LabelColumnName); 181return mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, labelColumnName: columnInfo.LabelColumnName); 203return mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryTrainer, labelColumnName: columnInfo.LabelColumnName); 224return mlContext.MulticlassClassification.Trainers.LbfgsMaximumEntropy(options); 242return mlContext.MulticlassClassification.Trainers.ImageClassification(options);
Microsoft.ML.AutoML.Samples (1)
AutoFit\MulticlassClassificationExperiment.cs (1)
40MulticlassClassificationMetrics testMetrics = mlContext.MulticlassClassification.Evaluate(testDataViewWithBestScore, labelColumnName: LabelColumnName);
Microsoft.ML.AutoML.Tests (1)
Utils\TaskAgnosticAutoFit.cs (1)
143var classificationMetrics = _context.MulticlassClassification.Evaluate(result.ScoredTestData, labelColumnName: label);
Microsoft.ML.Core.Tests (1)
UnitTests\TestEntryPoints.cs (1)
2014var mlr = ML.MulticlassClassification.Trainers.LbfgsMaximumEntropy();
Microsoft.ML.IntegrationTests (8)
Evaluation.cs (2)
154.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 162var metrics = mlContext.MulticlassClassification.Evaluate(scoredData);
IntrospectiveTraining.cs (1)
433.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy(
Training.cs (5)
270var trainer = mlContext.MulticlassClassification.Trainers.LbfgsMaximumEntropy( 458.Append(mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryClassificationTrainer)); 467var binaryClassificationMetrics = mlContext.MulticlassClassification.Evaluate(binaryClassificationPredictions); 489.Append(mlContext.MulticlassClassification.Trainers.OneVersusAll(binaryClassificationTrainer)) 499var binaryClassificationMetrics = mlContext.MulticlassClassification.Evaluate(binaryClassificationPredictions);
Microsoft.ML.OnnxTransformerTest (1)
DnnImageFeaturizerTest.cs (1)
230var trainer = ML.MulticlassClassification.Trainers.OneVersusAll(ML.BinaryClassification.Trainers.AveragedPerceptron(labelColumnName: "Label", numberOfIterations: 10, featureColumnName: "Features"), labelColumnName: "Label")
Microsoft.ML.PerformanceTests (6)
ImageClassificationBench.cs (1)
91var pipeline = _mlContext.MulticlassClassification.Trainers.ImageClassification(options)
PredictionEngineBench.cs (1)
59.Append(env.MulticlassClassification.Trainers.SdcaMaximumEntropy(
RffTransform.cs (2)
49.Append(mlContext.MulticlassClassification.Trainers.OneVersusAll(mlContext.BinaryClassification.Trainers.AveragedPerceptron(numberOfIterations: 10))); 51var cvResults = mlContext.MulticlassClassification.CrossValidate(data, pipeline, numberOfFolds: 5);
StochasticDualCoordinateAscentClassifierBench.cs (2)
80.Append(_mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy()); 118var trainer = _mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy();
Microsoft.ML.Samples (37)
Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (2)
66var pipeline = mlContext.MulticlassClassification.Trainers 160var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
Dynamic\Trainers\MulticlassClassification\ImageClassification\LearningRateSchedulingCifarResnetTransferLearning.cs (2)
102var pipeline = mlContext.MulticlassClassification.Trainers. 186var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (2)
93.Append(mlContext.MulticlassClassification.Trainers. 184var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (2)
82var pipeline = mlContext.MulticlassClassification.Trainers. 169var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
Dynamic\Trainers\MulticlassClassification\LbfgsMaximumEntropy.cs (2)
32.Append(mlContext.MulticlassClassification.Trainers 64var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\LbfgsMaximumEntropyWithOptions.cs (2)
40.Append(mlContext.MulticlassClassification.Trainers 72var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\LightGbm.cs (2)
35.Append(mlContext.MulticlassClassification.Trainers 67var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\LightGbmWithOptions.cs (2)
45.Append(mlContext.MulticlassClassification.Trainers 77var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\LogLossPerClass.cs (2)
32.Append(mlContext.MulticlassClassification.Trainers 47var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\NaiveBayes.cs (2)
38.Append(mlContext.MulticlassClassification.Trainers 70var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\OneVersusAll.cs (2)
32.Append(mlContext.MulticlassClassification.Trainers 65var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\PairwiseCoupling.cs (2)
32.Append(mlContext.MulticlassClassification.Trainers 65var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportance.cs (2)
32.Append(mlContext.MulticlassClassification.Trainers 46var permutationMetrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\PermutationFeatureImportanceLoadFromDisk.cs (2)
35.Append(mlContext.MulticlassClassification.Trainers 54var permutationMetrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\SdcaMaximumEntropy.cs (2)
40.Append(mlContext.MulticlassClassification.Trainers 72var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\SdcaMaximumEntropyWithOptions.cs (2)
49.Append(mlContext.MulticlassClassification.Trainers 81var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\SdcaNonCalibrated.cs (2)
40.Append(mlContext.MulticlassClassification.Trainers 72var metrics = mlContext.MulticlassClassification
Dynamic\Trainers\MulticlassClassification\SdcaNonCalibratedWithOptions.cs (2)
49.Append(mlContext.MulticlassClassification.Trainers 81var metrics = mlContext.MulticlassClassification
Dynamic\Transforms\Conversion\MapKeyToValueMultiColumn.cs (1)
34.Append(mlContext.MulticlassClassification.Trainers.
Microsoft.ML.Samples.GPU (8)
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ImageClassificationDefault.cs (2)
66var pipeline = mlContext.MulticlassClassification.Trainers 160var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\LearningRateSchedulingCifarResnetTransferLearning.cs (2)
102var pipeline = mlContext.MulticlassClassification.Trainers. 186var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningEarlyStopping.cs (2)
93.Append(mlContext.MulticlassClassification.Trainers. 184var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
docs\samples\Microsoft.ML.Samples\Dynamic\Trainers\MulticlassClassification\ImageClassification\ResnetV2101TransferLearningTrainTestSplit.cs (2)
82var pipeline = mlContext.MulticlassClassification.Trainers. 169var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
Microsoft.ML.TensorFlow.Tests (24)
TensorflowTests.cs (24)
155.Append(_mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy()); 161var metrics = _mlContext.MulticlassClassification.Evaluate(predictions); 671.Append(_mlContext.MulticlassClassification.Trainers.LightGbm("Label", "Features")); 675var metrics = _mlContext.MulticlassClassification.Evaluate(predicted); 725.Append(_mlContext.MulticlassClassification.Trainers.LightGbm("KeyLabel", "Features")); 729var metrics = _mlContext.MulticlassClassification.Evaluate(predicted, labelColumnName: "KeyLabel"); 841.Append(_mlContext.MulticlassClassification.Trainers.LightGbm(new Trainers.LightGbm.LightGbmMulticlassTrainer.Options() 851var metrics = _mlContext.MulticlassClassification.Evaluate(predicted); 895.Append(_mlContext.MulticlassClassification.Trainers.LightGbm("Label", "Features")); 899var metrics = _mlContext.MulticlassClassification.Evaluate(predicted); 1120.Append(_mlContext.MulticlassClassification.Trainers.NaiveBayes("Label", "Output")); 1122var cross = _mlContext.MulticlassClassification.CrossValidate(dataView, pipeline, 2); 1165.Append(_mlContext.MulticlassClassification.Trainers.NaiveBayes()); 1172var metrics = _mlContext.MulticlassClassification.Evaluate(transformedData); 1419.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification("Label", "Image") 1434var metrics = _mlContext.MulticlassClassification.Evaluate(predictions); 1522.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification(options) 1537var metrics = _mlContext.MulticlassClassification.Evaluate(predictions); 1680.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification(options)) 1696var metrics = _mlContext.MulticlassClassification.Evaluate(predictions); 1814.Append(_mlContext.MulticlassClassification.Trainers.ImageClassification(options)); 1826var metrics = _mlContext.MulticlassClassification.Evaluate(predictions); 1885var pipeline = _mlContext.MulticlassClassification.Trainers.ImageClassification(options); 1897var metrics = _mlContext.MulticlassClassification.Evaluate(predictions);
Microsoft.ML.Tests (101)
DatabaseLoaderTests.cs (5)
70.Append(mlContext.MulticlassClassification.Trainers.LightGbm()) 106.Append(mlContext.MulticlassClassification.Trainers.LightGbm()) 142.Append(mlContext.MulticlassClassification.Trainers.LightGbm()) 174.Append(mlContext.MulticlassClassification.Trainers.LightGbm()) 206.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy())
EvaluateTests.cs (2)
48var metrics = mlContext.MulticlassClassification.Evaluate(inputDV, topKPredictionCount: 4); 65var metrics2 = mlContext.MulticlassClassification.Evaluate(inputDV2, topKPredictionCount: 4);
OnnxConversionTest.cs (28)
631Append(mlContext.MulticlassClassification.Trainers.LbfgsMaximumEntropy(new LbfgsMaximumEntropyMulticlassTrainer.Options() { NumberOfThreads = 1 })); 1651mlContext.MulticlassClassification.Trainers.LbfgsMaximumEntropy(), 1652mlContext.MulticlassClassification.Trainers.NaiveBayes(), 1653mlContext.MulticlassClassification.Trainers.OneVersusAll( 1655mlContext.MulticlassClassification.Trainers.OneVersusAll( 1657mlContext.MulticlassClassification.Trainers.OneVersusAll( 1659mlContext.MulticlassClassification.Trainers.OneVersusAll( 1661mlContext.MulticlassClassification.Trainers.OneVersusAll( 1663mlContext.MulticlassClassification.Trainers.OneVersusAll( 1665mlContext.MulticlassClassification.Trainers.OneVersusAll( 1667mlContext.MulticlassClassification.Trainers.OneVersusAll( 1669mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy(), 1670mlContext.MulticlassClassification.Trainers.SdcaNonCalibrated() 1675estimators.Add(mlContext.MulticlassClassification.Trainers.LightGbm()); 1676estimators.Add(mlContext.MulticlassClassification.Trainers.LightGbm( 1978mlContext.MulticlassClassification.Trainers.LbfgsMaximumEntropy("Label", "MyFeatureVector"), 1979mlContext.MulticlassClassification.Trainers.NaiveBayes("Label", "MyFeatureVector"), 1980mlContext.MulticlassClassification.Trainers.OneVersusAll( 1982mlContext.MulticlassClassification.Trainers.OneVersusAll( 1984mlContext.MulticlassClassification.Trainers.OneVersusAll( 1986mlContext.MulticlassClassification.Trainers.OneVersusAll( 1988mlContext.MulticlassClassification.Trainers.OneVersusAll( 1990mlContext.MulticlassClassification.Trainers.OneVersusAll( 1992mlContext.MulticlassClassification.Trainers.OneVersusAll( 1994mlContext.MulticlassClassification.Trainers.OneVersusAll( 1996mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy("Label", "MyFeatureVector"), 1997mlContext.MulticlassClassification.Trainers.SdcaNonCalibrated("Label", "MyFeatureVector") 2002estimators.Add(mlContext.MulticlassClassification.Trainers.LightGbm("Label", "MyFeatureVector"));
PermutationFeatureImportanceTests.cs (10)
525var model = ML.MulticlassClassification.Trainers.LbfgsMaximumEntropy().Fit(data); 542pfi = ML.MulticlassClassification.PermutationFeatureImportance(castedModel, data); 543pfiDict = ml2.MulticlassClassification.PermutationFeatureImportance(loadedModel, data); 551pfi = ML.MulticlassClassification.PermutationFeatureImportance(model, data); 552pfiDict = ml2.MulticlassClassification.PermutationFeatureImportance((ITransformer)model, data); 597var model = ML.MulticlassClassification.Trainers.LbfgsMaximumEntropy( 615pfi = ML.MulticlassClassification.PermutationFeatureImportance(castedModel, data); 616pfiDict = ml2.MulticlassClassification.PermutationFeatureImportance(loadedModel, data); 624pfi = ML.MulticlassClassification.PermutationFeatureImportance(model, data); 625pfiDict = ml2.MulticlassClassification.PermutationFeatureImportance((ITransformer)model, data);
Scenarios\Api\CookbookSamples\CookbookSamplesDynamicApi.cs (4)
236.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy()); 652.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy()); 660var metrics = mlContext.MulticlassClassification.Evaluate(model.Transform(split.TestSet, TransformerScope.Everything)); 664var cvResults = mlContext.MulticlassClassification.CrossValidate(data, pipeline, numberOfFolds: 5);
Scenarios\Api\Estimators\DecomposableTrainAndPredict.cs (1)
35.Append(ml.MulticlassClassification.Trainers.SdcaMaximumEntropy(
Scenarios\Api\Estimators\Extensibility.cs (1)
44.Append(ml.MulticlassClassification.Trainers.SdcaMaximumEntropy(
Scenarios\Api\Estimators\PredictAndMetadata.cs (5)
33.Append(ml.MulticlassClassification.Trainers.SdcaMaximumEntropy( 82.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 89var metrics = mlContext.MulticlassClassification.Evaluate(scoredData); 116.Append(mlContext.MulticlassClassification.Trainers.OneVersusAll(singleTrainer)); 123var metrics2 = mlContext.MulticlassClassification.Evaluate(scoredData2);
Scenarios\IrisPlantClassificationTests.cs (2)
36.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 88var metrics = mlContext.MulticlassClassification.Evaluate(predicted, topKPredictionCount: 3);
Scenarios\IrisPlantClassificationWithStringLabelTests.cs (2)
40.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 90var metrics = mlContext.MulticlassClassification.Evaluate(predicted, topKPredictionCount: 3);
Scenarios\OvaTest.cs (8)
37var pipeline = mlContext.MulticlassClassification.Trainers.OneVersusAll(logReg, useProbabilities: false); 43var metrics = mlContext.MulticlassClassification.Evaluate(predictions); 73var pipeline = mlContext.MulticlassClassification.Trainers.OneVersusAll(ap, useProbabilities: false); 79var metrics = mlContext.MulticlassClassification.Evaluate(predictions); 106var pipeline = mlContext.MulticlassClassification.Trainers.OneVersusAll( 114var metrics = mlContext.MulticlassClassification.Evaluate(predictions); 140var pipeline = mlContext.MulticlassClassification.Trainers.OneVersusAll( 148var metrics = mlContext.MulticlassClassification.Evaluate(predictions);
ScenariosWithDirectInstantiation\IrisPlantClassificationTests.cs (2)
34.Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 48var metrics = mlContext.MulticlassClassification.Evaluate(predicted);
TrainerEstimators\LbfgsTests.cs (3)
36var trainer = ML.MulticlassClassification.Trainers.LbfgsMaximumEntropy(); 166var trainer = ML.MulticlassClassification.Trainers.LbfgsMaximumEntropy(); 185var trainer = ML.MulticlassClassification.Trainers.LbfgsMaximumEntropy(new LbfgsMaximumEntropyMulticlassTrainer.Options
TrainerEstimators\MetalinearEstimators.cs (4)
29var ova = ML.MulticlassClassification.Trainers.OneVersusAll(averagePerceptron, imputeMissingLabelsAsNegative: true, 49pipeline = pipeline.Append(ML.MulticlassClassification.Trainers.OneVersusAll(sdcaTrainer, useProbabilities: false)) 67pipeline = pipeline.Append(ML.MulticlassClassification.Trainers.PairwiseCoupling(sdcaTrainer)) 99.Append(ML.MulticlassClassification.Trainers.OneVersusAll(sdcaTrainer))
TrainerEstimators\SdcaTests.cs (10)
45var mcTrainer = ML.MulticlassClassification.Trainers.SdcaMaximumEntropy( 49var mcTrainerNonCalibrated = ML.MulticlassClassification.Trainers.SdcaNonCalibrated( 175Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 179Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy( 189var metrics1 = mlContext.MulticlassClassification.Evaluate(prediction1, labelColumnName: "LabelIndex", topKPredictionCount: 1); 190var metrics2 = mlContext.MulticlassClassification.Evaluate(prediction2, labelColumnName: "LabelIndex", topKPredictionCount: 1); 278Append(mlContext.MulticlassClassification.Trainers.SdcaMaximumEntropy(labelColumnName: "LabelIndex", featureColumnName: "Features", l2Regularization: 0.001f)); 285var metrics = mlContext.MulticlassClassification.Evaluate(prediction, labelColumnName: "LabelIndex", topKPredictionCount: 1); 312Append(mlContext.MulticlassClassification.Trainers.SdcaNonCalibrated(labelColumnName: "LabelIndex", featureColumnName: "Features", lossFunction: new HingeLoss(), l2Regularization: 0.001f)); 319var metrics = mlContext.MulticlassClassification.Evaluate(prediction, labelColumnName: "LabelIndex", topKPredictionCount: 1);
TrainerEstimators\TrainerEstimators.cs (1)
155pipe = pipe.Append(ML.MulticlassClassification.Trainers.NaiveBayes("Label", "Features"));
TrainerEstimators\TreeEnsembleFeaturizerTest.cs (2)
807.Append(ML.MulticlassClassification.Trainers.SdcaMaximumEntropy("KeyLabel", "CombinedFeatures")); 811var metrics = ML.MulticlassClassification.Evaluate(prediction, labelColumnName: "KeyLabel");
TrainerEstimators\TreeEstimators.cs (11)
309var trainer = ML.MulticlassClassification.Trainers.LightGbm(learningRate: 0.4); 326var trainer = ML.MulticlassClassification.Trainers.LightGbm(fStream); 349var trainer = ML.MulticlassClassification.Trainers.LightGbm(options); 365var trainer = ML.MulticlassClassification.Trainers.LightGbm(new LightGbmMulticlassTrainer.Options 390var trainer = ML.MulticlassClassification.Trainers.LightGbm(new LightGbmMulticlassTrainer.Options 409var trainer = ML.MulticlassClassification.Trainers.LightGbm(new LightGbmMulticlassTrainer.Options 747.Append(mlContext.MulticlassClassification.Trainers 780var trainer = ML.MulticlassClassification.Trainers.LightGbm(learningRate: 0.4); 784var metrics = ML.MulticlassClassification.Evaluate(model.Transform(dataView)); 1027var estimator = pipeline.Append(context.MulticlassClassification.Trainers.OneVersusAll(context.BinaryClassification.Trainers.FastTree())); 1112var trainer = pipeline.Append(context.MulticlassClassification.Trainers.LightGbm(
Microsoft.ML.TorchSharp.Tests (14)
NerTests.cs (3)
71.Append(ML.MulticlassClassification.Trainers.NamedEntityRecognition(outputColumnName: "outputColumn")) 150.Append(ML.MulticlassClassification.Trainers.NamedEntityRecognition(options)) 224.Append(ML.MulticlassClassification.Trainers.NamedEntityRecognition(options))
ObjectDetectionTests.cs (3)
51.Append(ML.MulticlassClassification.Trainers.ObjectDetection("Labels", boundingBoxColumnName: "Box", maxEpoch: 1)) 68.Append(ML.MulticlassClassification.Trainers.ObjectDetection(options)) 84var metrics = ML.MulticlassClassification.EvaluateObjectDetection(idv, idv.Schema[2], idv.Schema["Box"], idv.Schema["PredictedLabel"], idv.Schema["PredictedBoundingBoxes"], idv.Schema["Score"]);
QATests.cs (2)
43var estimator = chain.Append(ML.MulticlassClassification.Trainers.QuestionAnswer(maxEpochs: 1)); 87var estimator = ML.MulticlassClassification.Trainers.QuestionAnswer(maxEpochs: 30);
TextClassificationTests.cs (6)
99.Append(ML.MulticlassClassification.Trainers.TextClassification(outputColumnName: "outputColumn")) 156var metrics = ML.MulticlassClassification.Evaluate(transformer.Transform(dataView, TransformerScope.Everything), predictedLabelColumnName: "outputColumn"); 178.Append(mlContext.MulticlassClassification.Trainers.TextClassification(sentence1ColumnName: "Title", sentence2ColumnName: "Description", maxEpochs: 10, batchSize: 8)) 182var metrics = mlContext.MulticlassClassification.Evaluate(predictionIdv); 236.Append(ML.MulticlassClassification.Trainers.TextClassification(outputColumnName: "outputColumn")) 320var estimator = ML.MulticlassClassification.Trainers.TextClassification(outputColumnName: "outputColumn", sentence1ColumnName: "Sentence", sentence2ColumnName: "Sentence2", validationSet: preppedData)