private ISingleFeaturePredictionTransformer <TScalarPredictor> TrainOne(IChannel ch, TScalarTrainer trainer, RoleMappedData data, int cls)
{
var view = MapLabels(data, cls);
string trainerLabel = data.Schema.Label.Name;
// REVIEW: In principle we could support validation sets and the like via the train context, but
// this is currently unsupported.
var transformer = trainer.Fit(view);
if (_args.UseProbabilities)
{
var calibratedModel = transformer.Model as TDistPredictor;
// REVIEW: restoring the RoleMappedData, as much as we can.
// not having the weight column on the data passed to the TrainCalibrator should be addressed.
var trainedData = new RoleMappedData(view, label: trainerLabel, feature: transformer.FeatureColumn);
if (calibratedModel == null)
{
calibratedModel = CalibratorUtils.TrainCalibrator(Host, ch, Calibrator, Args.MaxCalibrationExamples, transformer.Model, trainedData) as TDistPredictor;
}
Host.Check(calibratedModel != null, "Calibrated predictor does not implement the expected interface");
return(new BinaryPredictionTransformer <TScalarPredictor>(Host, calibratedModel, trainedData.Data.Schema, transformer.FeatureColumn));
}
return(new BinaryPredictionTransformer <TScalarPredictor>(Host, transformer.Model, view.Schema, transformer.FeatureColumn));
}
private ISingleFeaturePredictionTransformer<TDistPredictor> TrainOne(IChannel ch, TScalarTrainer trainer, RoleMappedData data, int cls1, int cls2)
{
// this should not be necessary when the legacy constructor doesn't exist, and the label column is not an optional parameter on the
// MetaMulticlassTrainer constructor.
string trainerLabel = data.Schema.Label.Value.Name;
var view = MapLabels(data, cls1, cls2);
var transformer = trainer.Fit(view);
// the validations in the calibrator check for the feature column, in the RoleMappedData
var trainedData = new RoleMappedData(view, label: trainerLabel, feature: transformer.FeatureColumnName);
var calibratedModel = transformer.Model as TDistPredictor;
if (calibratedModel == null)
calibratedModel = CalibratorUtils.GetCalibratedPredictor(Host, ch, Calibrator, transformer.Model, trainedData, Args.MaxCalibrationExamples) as TDistPredictor;
return new BinaryPredictionTransformer<TDistPredictor>(Host, calibratedModel, trainedData.Data.Schema, transformer.FeatureColumnName);
}
