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();
}
