public void AdjustTreeOutputs(IChannel ch, InternalRegressionTree tree,
DocumentPartitioning partitioning, ScoreTracker trainingScores)
{
const double epsilon = 1.4e-45;
double multiplier = LearningRate * Shrinkage;
double[] means = null;
if (!BestStepRankingRegressionTrees)
{
means = _parallelTraining.GlobalMean(Dataset, tree, partitioning, Weights, false);
}
for (int l = 0; l < tree.NumLeaves; ++l)
{
double output = tree.GetOutput(l);
if (BestStepRankingRegressionTrees)
{
output *= multiplier;
}
else
{
output = multiplier * (output + epsilon) / (means[l] + epsilon);
}
if (output > MaxTreeOutput)
{
output = MaxTreeOutput;
}
else if (output < -MaxTreeOutput)
{
output = -MaxTreeOutput;
}
tree.SetOutput(l, output);
}
}
internal override void AddScores(InternalRegressionTree tree, double multiplier)
{
_k++;
double coeff = (_k - 1.0) / (_k + 2.0);
int innerLoopSize = 1 + Dataset.NumDocs / BlockingThreadPool.NumThreads; // +1 is to make sure we don't have a few left over at the end
// REVIEW: This partitioning doesn't look optimal.
// Probably make sence to investigate better ways of splitting data?
var actions = new Action[(int)Math.Ceiling(1.0 * Dataset.NumDocs / innerLoopSize)];
var actionIndex = 0;
for (int d = 0; d < Dataset.NumDocs; d += innerLoopSize)
{
var fromDoc = d;
var toDoc = Math.Min(d + innerLoopSize, Dataset.NumDocs);
actions[actionIndex++] = () =>
{
var featureBins = Dataset.GetFeatureBinRowwiseIndexer();
for (int doc = fromDoc; doc < toDoc; doc++)
{
double output = multiplier * tree.GetOutput(featureBins[doc]);
double newXK = YK[doc] + output;
double newYK = newXK + coeff * (newXK - XK[doc]);
XK[doc] = newXK;
YK[doc] = newYK;
}
};
}
Parallel.Invoke(new ParallelOptions {
MaxDegreeOfParallelism = BlockingThreadPool.NumThreads
}, actions);
SendScoresUpdatedMessage();
}
public void AdjustTreeOutputs(IChannel ch, InternalRegressionTree tree, DocumentPartitioning partitioning, ScoreTracker trainingScores)
{
double shrinkage = LearningRate * Shrinkage;
for (int l = 0; l < tree.NumLeaves; ++l)
{
double output = tree.GetOutput(l) * shrinkage;
tree.SetOutput(l, output);
}
}
