public override IRegressionModel Build(IRegressionProblemData pd, IRandom random,
CancellationToken cancellationToken, out int numberOfParameters)
{
var pca = PrincipleComponentTransformation.CreateProjection(pd.Dataset, pd.TrainingIndices, pd.AllowedInputVariables, normalize: true);
var pcdata = pca.TransformProblemData(pd);
ComponentReducedLinearModel bestModel = null;
var bestCvrmse = double.MaxValue;
numberOfParameters = 1;
for (var i = 1; i <= Math.Min(NumberOfComponents, pd.AllowedInputVariables.Count()); i++)
{
var pd2 = (IRegressionProblemData)pcdata.Clone();
var inputs = new HashSet <string>(pca.ComponentNames.Take(i));
foreach (var v in pd2.InputVariables.CheckedItems.ToArray())
{
pd2.InputVariables.SetItemCheckedState(v.Value, inputs.Contains(v.Value.Value));
}
double rmse;
var model = PreconstructedLinearModel.CreateLinearModel(pd2, out rmse);
if (rmse > bestCvrmse)
{
continue;
}
bestModel = new ComponentReducedLinearModel(pd2.TargetVariable, model, pca);
numberOfParameters = i + 1;
bestCvrmse = rmse;
}
return(bestModel);
}
private ComponentReducedLinearModel(ComponentReducedLinearModel original, Cloner cloner) : base(original, cloner)
{
Model = cloner.Clone(original.Model);
Pca = cloner.Clone(original.Pca);
}
