public static CommonOutputs.RegressionOutput CreateRegressionEnsemble(IHostEnvironment env, RegressionInput input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("CombineModels");
host.CheckValue(input, nameof(input));
host.CheckNonEmpty(input.Models, nameof(input.Models));
GetPipeline(host, input, out IDataView startingData, out RoleMappedData transformedData);
var args = new RegressionEnsembleTrainer.Arguments();
switch (input.ModelCombiner)
{
case ScoreCombiner.Median:
args.OutputCombiner = new MedianFactory();
break;
case ScoreCombiner.Average:
args.OutputCombiner = new AverageFactory();
break;
default:
throw host.Except("Unknown combiner kind");
}
var trainer = new RegressionEnsembleTrainer(host, args);
var ensemble = trainer.CombineModels(input.Models.Select(pm => pm.Predictor as IPredictorProducing <float>));
var predictorModel = new PredictorModel(host, transformedData, startingData, ensemble);
var output = new CommonOutputs.RegressionOutput {
PredictorModel = predictorModel
};
return(output);
}
public static CommonOutputs.RegressionOutput CreateRegressionEnsemble(IHostEnvironment env, RegressionEnsembleTrainer.Arguments input)
{
Contracts.CheckValue(env, nameof(env));
var host = env.Register("TrainRegressionEnsemble");
host.CheckValue(input, nameof(input));
EntryPointUtils.CheckInputArgs(host, input);
return(LearnerEntryPointsUtils.Train <RegressionEnsembleTrainer.Arguments, CommonOutputs.RegressionOutput>(host, input,
() => new RegressionEnsembleTrainer(host, input),
() => LearnerEntryPointsUtils.FindColumn(host, input.TrainingData.Schema, input.LabelColumn)));
}
