[MRG] Multi-layer perceptron (MLP)

<h1>Multi-layer perceptron (MLP)</h1>
![mlp](https://f.cloud.github.com/assets/3382128/727899/5112c4dc-e1cb-11e2-8eaa-fe9b87bd9724.jpg)

<note>This is an extention to larsmans code.</note>

A multilayer perceptron (MLP) is a feedforward artificial neural network model that tries to learn a function f(X)=y where y is the output and X is the input. An MLP consists of multiple layers, usually of one hidden layer, an input layer and an output layer, where each layer is fully connected to the next one. This is a classic algorithm that has been extensively used in Neural Networks.

<h3>Code Check out :</h3>
1) git clone https://github.com/scikit-learn/scikit-learn
2) cd scikit-learn/
3) git fetch origin refs/pull/2120/head:mlp
4) git checkout mlp 

<h3>Tutorial link:</h3>
- http://easymachinelearning.blogspot.com/p/multi-layer-perceptron-tutorial.html

<h3>Sample Benchmark:</h3>
- `MLP` on the scikit's `Digits` dataset gives,
 - Score for `tanh-based sgd`: 0.981
 -  Score for `logistic-based sgd`: 0.987
 -  Score for `tanh-based l-bfgs`: 0.994
 -  Score for `logistic-based l-bfgs`: 1.000

<h3>TODO:</h3>
- Review