public void train(int[] instanceLengths, String trainfile, File train_forest) throws IOException {
// System.out.print("About to train. ");
// System.out.print("Num Feats: " + pipe.dataAlphabet.size());
int i = 0;
for (i = 0; i < options.numIters; i++) {
System.out.print(" Iteration " + i);
// System.out.println("========================");
// System.out.println("Iteration: " + i);
// System.out.println("========================");
System.out.print("[");
long start = System.currentTimeMillis();
trainingIter(instanceLengths, trainfile, train_forest, i + 1);
long end = System.currentTimeMillis();
// System.out.println("Training iter took: " + (end-start));
System.out.println("|Time:" + (end - start) + "]");
}
params.averageParams(i * instanceLengths.length);
}
public void train(int[] instanceLengths, int[] ignore, String trainfile, File train_forest)
throws IOException {
int i = 0;
for (i = 0; i < options.numIters; i++) {
System.out.print(" Iteration " + i);
System.out.print("[");
long start = System.currentTimeMillis();
trainingIter(instanceLengths, ignore, trainfile, train_forest, i + 1);
long end = System.currentTimeMillis();
// System.out.println("Training iter took: " + (end-start));
System.out.println("|Time:" + (end - start) + "]");
}
params.averageParams(i * countActualInstances(ignore));
// afm 06-04-08
if (options.separateLab) {
LabelClassifier oc =
new LabelClassifier(
options, instanceLengths, ignore, trainfile, train_forest, this, pipe);
try {
classifier = oc.trainClassifier(100);
} catch (Exception e) {
e.printStackTrace();
}
}
}
