protected void updateTreeOutput(RegressionTree rt) {
List<Split> leaves = rt.leaves();
for (int i = 0; i < leaves.size(); i++) {
float s1 = 0.0F;
Split s = leaves.get(i);
int[] idx = s.getSamples();
for (int j = 0; j < idx.length; j++) {
int k = idx[j];
s1 += pseudoResponses[k];
}
s.setOutput(s1 / idx.length);
}
}
/**
* Each input node @n corersponds to a <split> tag in the model file.
*
* @param n
* @return
*/
private Split create(Node n) {
Split s = null;
if (n.getFirstChild().getNodeName().compareToIgnoreCase("feature") == 0) // this is a split
{
NodeList nl = n.getChildNodes();
int fid =
Integer.parseInt(
nl.item(0).getFirstChild().getNodeValue().toString().trim()); // <feature>
float threshold =
Float.parseFloat(
nl.item(1).getFirstChild().getNodeValue().toString().trim()); // <threshold>
s = new Split(fid, threshold, 0);
s.setLeft(create(nl.item(2)));
s.setRight(create(nl.item(3)));
} else // this is a stump
{
float output =
Float.parseFloat(n.getFirstChild().getFirstChild().getNodeValue().toString().trim());
s = new Split();
s.setOutput(output);
}
return s;
}
