protected virtual IDecisionTreeNode BuildDecisionNode(
IDataFrame dataFrame,
string dependentFeatureName,
IDecisionTreeModelBuilderParams additionalParams,
IAlredyUsedAttributesInfo alreadyUsedAttributesInfo,
int treeDepth,
bool isFirstSplit = false)
{
if (dataFrame.GetColumnVector <object>(dependentFeatureName).DataItems.Distinct().Count() == 1 || MaximalTreeDepthHasBeenReached(additionalParams, treeDepth))
{
return(BuildLeaf(dataFrame, dependentFeatureName));
}
// TODO: later on add additional params indicating which features were already used
ISplittingResult splitResult = BestSplitSelector.SelectBestSplit(
dataFrame,
dependentFeatureName,
SplitQualityChecker,
alreadyUsedAttributesInfo);
if (SplitIsEmpty(splitResult))
{
return(BuildLeaf(dataFrame, dependentFeatureName));
}
if (additionalParams.UsePrunningHeuristicDuringTreeBuild && this.StatisticalSignificanceChecker != null)
{
var isSplitSignificant = StatisticalSignificanceChecker.IsSplitStatisticallySignificant(
dataFrame,
splitResult,
dependentFeatureName);
if (!isSplitSignificant)
{
return(BuildLeaf(dataFrame, dependentFeatureName));
}
}
var children = new ConcurrentDictionary <IDecisionTreeLink, IDecisionTreeNode>();
if (isFirstSplit)
{
Parallel.ForEach(
splitResult.SplittedDataSets,
splitData =>
{
this.AddChildFromSplit(dependentFeatureName, additionalParams, splitData, children, alreadyUsedAttributesInfo, treeDepth + 1);
});
}
else
{
foreach (var splitData in splitResult.SplittedDataSets)
{
this.AddChildFromSplit(dependentFeatureName, additionalParams, splitData, children, alreadyUsedAttributesInfo, treeDepth + 1);
}
}
return(BuildConcreteDecisionTreeNode(splitResult, children));
}
