protected DampenedModel(DampenedModel original, Cloner cloner) : base(original, cloner)
{
Model = cloner.Clone(original.Model);
Min = original.Min;
Max = original.Max;
Dampening = original.Dampening;
}
public IRegressionModel BuildModel(IReadOnlyList <int> rows, RegressionTreeParameters parameters, CancellationToken cancellation, out int numberOfParameters)
{
var reducedData = RegressionTreeUtilities.ReduceDataset(parameters.Data, rows, parameters.AllowedInputVariables.ToArray(), parameters.TargetVariable);
var pd = new RegressionProblemData(reducedData, parameters.AllowedInputVariables.ToArray(), parameters.TargetVariable);
pd.TrainingPartition.Start = 0;
pd.TrainingPartition.End = pd.TestPartition.Start = pd.TestPartition.End = reducedData.Rows;
int numP;
var model = Build(pd, parameters.Random, cancellation, out numP);
if (UseDampening && Dampening > 0.0)
{
model = DampenedModel.DampenModel(model, pd, Dampening);
}
numberOfParameters = numP;
cancellation.ThrowIfCancellationRequested();
return(model);
}