I'm studying Spark MLlib. While studying DecisionTree, I see following DecisionTree.trainClassifier usage example.
import org.apache.spark.mllib.tree._
val model = DecisionTree.trainClassifier(trainData, 7, Map[int, int](), "gini", 4, 100)
There are 6 parameters here, I don't understand the 3rd(Map), 5th(4) and 6th(100) parameters.
Google says they are categorical feature, lambda and alpha. Can anyone explain them a bit better?
need your kind help