[SPARK-2478] [mllib] DecisionTree Python API

Added experimental Python API for Decision Trees.

API:
* class DecisionTreeModel
** predict() for single examples and RDDs, taking both feature vectors and LabeledPoints
** numNodes()
** depth()
** __str__()
* class DecisionTree
** trainClassifier()
** trainRegressor()
** train()

Examples and testing:
* Added example testing classification and regression with batch prediction: examples/src/main/python/mllib/tree.py
* Have also tested example usage in doc of python/pyspark/mllib/tree.py which tests single-example prediction with dense and sparse vectors

Also: Small bug fix in python/pyspark/mllib/_common.py: In _linear_predictor_typecheck, changed check for RDD to use isinstance() instead of type() in order to catch RDD subclasses.

CC @mengxr @manishamde
It is really hard to guess what this method does until I read the code in main. So more doc is needed. Another option is to remove it and use it in unit test, because people will use this as a template to build their own applications. Swapping the first feature with the label is not a common operation.