Initial commit for multilayer perceptron.

* added mlp to sklearn/__init__.py
* created sklearn/mlp/setup.py and added to sklearn/setup.py
* created squared loss function in mlp_fast.pyx
Implemented basic sgd and created MLP classifier.
Fixed source code with help from pylint
Added multinomial cross-entropy loss.

* Added cross-entropy loss function
* Added softmax output function
* cross-entropy and softmax are default for classifier
* softmax doesn't work for binomial
Added additional loss functions and tests.

* Added cross-entropy and multinomial cross-entropy loss function
* Added softmax and logsig output functions
* Modified tests to be more robust
* Compared performance with pure implementation
Formatting tweaks
FIX: wrong computation of delta_h
Comparing implementations with same initialization
Separated backward step, eliminated array creation in tanh
forward and backward are now python functions
fixed computing gradient
Added shuffle_data attribute
correct cross entropy loss
Fixed dimensions for layer
Added gradient checking and momentum term.