public PipelineNode CreatePipelineNode(IEnumerable <SweepableParam> sweepParams, ColumnInformation columnInfo)
{
return(TrainerExtensionUtil.BuildLightGbmPipelineNode(TrainerExtensionCatalog.GetTrainerName(this), sweepParams,
columnInfo.LabelColumnName, columnInfo.ExampleWeightColumnName));
}
public ITrainerEstimator CreateInstance(MLContext mlContext, IEnumerable <SweepableParam> sweepParams,
ColumnInformation columnInfo, IDataView validationSet)
{
LightGbmMulticlassTrainer.Options options = TrainerExtensionUtil.CreateLightGbmOptions <LightGbmMulticlassTrainer.Options, VBuffer <float>, MulticlassPredictionTransformer <OneVersusAllModelParameters>, OneVersusAllModelParameters>(sweepParams, columnInfo);
return(mlContext.MulticlassClassification.Trainers.LightGbm(options));
}
public ITrainerEstimator CreateInstance(MLContext mlContext, IEnumerable <SweepableParam> sweepParams,
ColumnInformation columnInfo, IDataView validationSet)
{
LightGbmRegressionTrainer.Options options = TrainerExtensionUtil.CreateLightGbmOptions <LightGbmRegressionTrainer.Options, float, RegressionPredictionTransformer <LightGbmRegressionModelParameters>, LightGbmRegressionModelParameters>(sweepParams, columnInfo);
return(mlContext.Regression.Trainers.LightGbm(options));
}
public PipelineNode CreatePipelineNode(IEnumerable <SweepableParam> sweepParams, ColumnInformation columnInfo)
{
return(TrainerExtensionUtil.BuildOvaPipelineNode(this, _binaryLearnerCatalogItem, sweepParams, columnInfo));
}
public ITrainerEstimator CreateInstance(MLContext mlContext, IEnumerable <SweepableParam> sweepParams,
ColumnInformation columnInfo)
{
LightGbmBinaryTrainer.Options options = TrainerExtensionUtil.CreateLightGbmOptions <LightGbmBinaryTrainer.Options, float, BinaryPredictionTransformer <CalibratedModelParametersBase <LightGbmBinaryModelParameters, PlattCalibrator> >, CalibratedModelParametersBase <LightGbmBinaryModelParameters, PlattCalibrator> >(sweepParams, columnInfo);
return(mlContext.BinaryClassification.Trainers.LightGbm(options));
}