public void OVAWithAllConstructorArgs() { var(pipeline, data) = GetMultiClassPipeline(); var calibrator = new PlattCalibratorTrainer(Env); var averagePerceptron = new AveragedPerceptronTrainer(Env, new AveragedPerceptronTrainer.Arguments { FeatureColumn = "Features", LabelColumn = "Label", Shuffle = true, Calibrator = null }); pipeline.Append(new Ova(Env, averagePerceptron, "Label", true, calibrator: calibrator, 10000, true)) .Append(new KeyToValueEstimator(Env, "PredictedLabel")); TestEstimatorCore(pipeline, data); Done(); }
public void OVAWithAllConstructorArgs() { var(pipeline, data) = GetMultiClassPipeline(); var calibrator = new PlattCalibratorTrainer(Env); var averagePerceptron = ML.BinaryClassification.Trainers.AveragedPerceptron( new AveragedPerceptronTrainer.Options { Shuffle = true, Calibrator = null }); pipeline = pipeline.Append(new Ova(Env, averagePerceptron, "Label", true, calibrator: calibrator, 10000, true)) .Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); TestEstimatorCore(pipeline, data); Done(); }
public void OVAWithAllConstructorArgs() { var(pipeline, data) = GetMultiClassPipeline(); var calibrator = new PlattCalibratorTrainer(Env); var averagePerceptron = new AveragedPerceptronTrainer(Env, "Label", "Features", advancedSettings: s => { s.Shuffle = true; s.Calibrator = null; }); pipeline.Append(new Ova(Env, averagePerceptron, "Label", true, calibrator: calibrator, 10000, true)) .Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); TestEstimatorCore(pipeline, data); Done(); }
public void OVAWithAllConstructorArgs() { var(pipeline, data) = GetMultiClassPipeline(); var calibrator = new PlattCalibratorTrainer(Env); var averagePerceptron = ML.BinaryClassification.Trainers.AveragedPerceptron( new AveragedPerceptronTrainer.Options { Shuffle = true, Calibrator = null }); var ova = ML.MulticlassClassification.Trainers.OneVersusAll(averagePerceptron, imputeMissingLabelsAsNegative: true, calibrator: calibrator, maxCalibrationExamples: 10000, useProbabilities: true); pipeline = pipeline.Append(ova) .Append(new KeyToValueMappingEstimator(Env, "PredictedLabel")); TestEstimatorCore(pipeline, data); Done(); }