private static TOut CreatePipelineEnsemble <TOut>(IHostEnvironment env, PredictorModel[] predictors, SchemaBindablePipelineEnsembleBase ensemble)
where TOut : CommonOutputs.TrainerOutput, new()
{
var inputSchema = predictors[0].TransformModel.InputSchema;
var dv = new EmptyDataView(env, inputSchema);
// The role mappings are specific to the individual predictors.
var rmd = new RoleMappedData(dv);
var predictorModel = new PredictorModelImpl(env, rmd, dv, ensemble);
var output = new TOut {
PredictorModel = predictorModel
};
return(output);
}
public static CommonOutputs.BinaryClassificationOutput CreateBinaryEnsemble(IHostEnvironment env, ClassifierInput 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 EnsembleTrainer.Arguments();
switch (input.ModelCombiner)
{
case ClassifierCombiner.Median:
args.OutputCombiner = new MedianFactory();
break;
case ClassifierCombiner.Average:
args.OutputCombiner = new AverageFactory();
break;
case ClassifierCombiner.Vote:
args.OutputCombiner = new VotingFactory();
break;
default:
throw host.Except("Unknown combiner kind");
}
var trainer = new EnsembleTrainer(host, args);
var ensemble = trainer.CombineModels(input.Models.Select(pm => pm.Predictor as IPredictorProducing <float>));
var predictorModel = new PredictorModelImpl(host, transformedData, startingData, ensemble);
var output = new CommonOutputs.BinaryClassificationOutput {
PredictorModel = predictorModel
};
return(output);
}
