[MRG] Generic multi layer perceptron

Currently I am implementing `layers_coef_` to allow for any number of hidden layers.

This pull request is to implement the generic Multi-layer perceptron as part of the GSoC 2014 proposal. 

The expected time to finish this pull request is June 15

The goal is to extend Multi-layer Perceptron to support more than one hidden layer and to support having a pre-training phase (initializing weights through Restricted Boltzmann Machines) and a fine-tuning phase; and write its documentation.

This directly follows from this pull-request: https://github.com/scikit-learn/scikit-learn/pull/2120
Thanks @jnothman . I read all about the issues with having lists of lists for multi-label instances - it makes sense why its support is being deprecated.

I was having problems with `make_multilabel_classification`, but by setting `return_indicator` to `True`, it returned a friendly format for `LabelBinarizer` that worked nicely. Thanks :)