// Divides output values of leaves to bag count.
// This brings back the final scores generated by model on a same
// range as when we didn't use bagging
public void ScaleEnsembleLeaves(int numTrees, int bagSize, TreeEnsemble ensemble)
{
int bagCount = GetBagCount(numTrees, bagSize);
for (int t = 0; t < ensemble.NumTrees; t++)
{
RegressionTree tree = ensemble.GetTreeAt(t);
tree.ScaleOutputsBy(1.0 / bagCount);
}
}
private TreeEnsemble GetEnsembleFromSolution(LassoFit fit, int solutionIdx, TreeEnsemble originalEnsemble)
{
TreeEnsemble ensemble = new TreeEnsemble();
int weightsCount = fit.NumberOfWeights[solutionIdx];
for (int i = 0; i < weightsCount; i++)
{
double weight = fit.CompressedWeights[solutionIdx][i];
if (weight != 0)
{
RegressionTree tree = originalEnsemble.GetTreeAt(fit.Indices[i]);
tree.Weight = weight;
ensemble.AddTree(tree);
}
}
ensemble.Bias = fit.Intercepts[solutionIdx];
return(ensemble);
}
