[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
Oh yah, because it is being called in two methods: `partial_fit` and `fit`. :)

Just like for ELM, I wish I could combine `partial_fit` and `fit` together but they only have similarity at the beginning since they are quite different at the second half. I believe you are seeing a way to combine them that I don't :)