DecisionTrees.hs

buildTreeAtLevel  :: (Examples -> Double) -> PB.SplittingConstraints -> Int -> Examples -> DecisionTree
buildTreeAtLevel leafWeight splittingConstraints level examples =
    if shouldSplit splittingConstraints level examples bestSplit
    then Branch {
               _feature=_splitFeature bestSplit
             , _value=_splitValue bestSplit
             , _left=recur $ V.takeWhile takePredicate orderedExamples
             , _right=recur $ V.dropWhile takePredicate orderedExamples
             }
    else Leaf (leafWeight examples) where
        -- candidate splits
        candidates = V.map (findBestSplit examples) (getFeatures examples)
        -- best candidate from all the features
        bestSplit = V.maximumBy (compare `on` _averageGain) candidates
        -- sort the examples at this branch by the best feature
        orderedExamples = sortFeature examples (_splitFeature bestSplit)
        -- left branch takes <, right branch takes >
        takePredicate ex = features' ex ! _splitFeature bestSplit < _splitValue bestSplit
        -- construct the next level of the tree
        recur = buildTreeAtLevel leafWeight splittingConstraints (level + 1)