DecisionTree

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Static methods

def deserialize(encodedTree: Rep[String]): Rep[DecisionTree]

Infix methods

def addNode(parent: Rep[Int], isLeft: Rep[Boolean], isLeaf: Rep[Boolean], feature: Rep[Int], threshold: Rep[Double], impurity: Rep[Double], numNodeSamples: Rep[Int]): Rep[Int]

def capacity(): Rep[Int]

def feature(): Rep[ForgeArray[Int]]

def impurity(): Rep[ForgeArray[Double]]

def isLeaf(): Rep[ForgeArray[Boolean]]

def leftChildren(): Rep[ForgeArray[Int]]

def numNodeSamples(): Rep[ForgeArray[Int]]

def numNodes(): Rep[Int]

def pprint(): Rep[Unit]

def predict(testPt: Rep[DenseVector[Double]]): Rep[Tup2[Double,:doc:double]]

def prob(): Rep[ForgeArray[Double]]

def rightChildren(): Rep[ForgeArray[Int]]

 def serialize(): Rep[String]

For now we use a simple text-format to persist the tree. Eventually, we probably will want to switch to a binary format for efficiency in saving and loading large forests.

def threshold(): Rep[ForgeArray[Double]]

def value(): Rep[ForgeArray[Double]]