[SPARK-4979][MLLIB] Streaming logisitic regression

This adds support for streaming logistic regression with stochastic gradient descent, in the same manner as the existing implementation of streaming linear regression. It is a relatively simple addition because most of the work is already done by the abstract class `StreamingLinearAlgorithm` and existing algorithms and models from MLlib.

The PR includes
- Streaming Logistic Regression algorithm
- Unit tests for accuracy, streaming convergence, and streaming prediction
- An example use

cc mengxr tdas

Author: freeman <the.freeman.lab@gmail.com>

Closes #4306 from freeman-lab/streaming-logisitic-regression and squashes the following commits:

5c2c70b [freeman] Use Option on model
5cca2bc [freeman] Merge remote-tracking branch 'upstream/master' into streaming-logisitic-regression
275f8bd [freeman] Make private to mllib
3926e4e [freeman] Line formatting
5ee8694 [freeman] Experimental tag for docs
2fc68ac [freeman] Fix example formatting
85320b1 [freeman] Fixed line length
d88f717 [freeman] Remove stray comment
59d7ecb [freeman] Add streaming logistic regression
e78fe28 [freeman] Add streaming logistic regression example
321cc66 [freeman] Set private and protected within mllib