// Implementation for cached computation of weighted output
// (used by smoothing)
public double GetWeightedOutput()
{
if (!double.IsNaN(_weightedOutput))
{
return(_weightedOutput);
}
if (NodeIndex < 0)
{
return(Tree.GetOutput(~NodeIndex));
}
int lteDocCount = LteNode.GetDocumentCount();
int gtCount = GtNode.GetDocumentCount();
_weightedOutput = (lteDocCount * LteNode.GetWeightedOutput() + gtCount * GtNode.GetWeightedOutput())
/ (lteDocCount + gtCount);
return(_weightedOutput);
}
/// <summary>
/// Regularize a regression tree with smoothing paramter alpha.
/// </summary>
protected virtual void SmoothTree(InternalRegressionTree tree, double smoothing)
{
if (smoothing == 0.0)
{
return;
}
//Create recursive structure of the tree starting from root node
var regularizer = new RecursiveRegressionTree(tree, TreeLearner.Partitioning, 0);
//Perform bottom-up computation of weighted interior node output
double rootNodeOutput = regularizer.GetWeightedOutput();
//followed by top-down propagation of parent's output value
regularizer.SmoothLeafOutputs(rootNodeOutput, smoothing);
}
