public void FindGlobalBestSplit(LeafSplitCandidates smallerChildSplitCandidates,
LeafSplitCandidates largerChildSplitCandidates,
FindBestThresholdFromRawArrayFun findFunction,
SplitInfo[] bestSplits)
{
return;
}
public void FindGlobalBestSplit(LeafSplitCandidates smallerChildSplitCandidates,
LeafSplitCandidates largerChildSplitCandidates,
Microsoft.ML.Runtime.FastTree.FindBestThresholdFromRawArrayFun findFunction,
SplitInfo[] bestSplits)
{
Assert.True(_isInitEnv);
Assert.True(_isInitTreeLearner);
Assert.True(_isInitIteration);
Assert.True(_isCache);
_isCache = false;
Assert.NotNull(smallerChildSplitCandidates);
Assert.NotNull(bestSplits);
return;
}
protected override void FindAndSetBestFeatureForLeaf(LeafSplitCandidates leafSplitCandidates)
{
if (SoftmaxTemperature != 0 || SplitFraction == 1.0)
{
base.FindAndSetBestFeatureForLeaf(leafSplitCandidates);
return;
}
// REVIEW: Stupid, but changing actually changes all
// FastForeset baselines. Improve later.
var infos = leafSplitCandidates.FeatureSplitInfo;
int bestFeature = 0;
double max = infos[0].Gain;
for (int i = 1; i < infos.Length; ++i)
{
if (infos[i].Gain > max && Rand.NextDouble() < SplitFraction || Double.IsNegativeInfinity(max))
{
max = infos[bestFeature = i].Gain;
}
}
SetBestFeatureForLeaf(leafSplitCandidates, bestFeature);
}
void IParallelTraining.FindGlobalBestSplit(LeafSplitCandidates smallerChildSplitCandidates,
LeafSplitCandidates largerChildSplitCandidates,
FindBestThresholdFromRawArrayFun findFunction,
SplitInfo[] bestSplits)
{
}