Bug Fix: without unpersist method in RandomForest.scala

During trainning Gradient Boosting Decision Tree on large-scale sparse data, spark spill hundreds of data onto disk. And find the bug below:
    In version 1.1.0 DecisionTree.scala, train Method, treeInput has been persisted in Memory, but without unpersist. It caused heavy DISK usage.
    In github version(1.2.0 maybe), RandomForest.scala, train Method, baggedInput has been persisted but without unpersisted too.

After added unpersist, it works right.
https://issues.apache.org/jira/browse/SPARK-3918