[MRG] GSoC 2014: Standard Extreme Learning Machines

Finished implementing the standard extreme learning machines (ELMs). I am getting the following results with 550 hidden neurons against the digits datasets,

Training accuracy using the logistic activation function: 0.999444
Training accuracy using the tanh activation function: 1.000000

Fortunately, this algorithm is much easier to implement and debug than multi-layer perceptron :).
I will push a test file soon.

@ogrisel , @larsmans
Waw, thanks @ogrisel. `Matplotlib` is certainly the way to go for plotting diagrams.

I just implemented a generic method that draws a network with any number of layers and neurons and scales
them accordingly.

These are two examples,
![slfn](https://cloud.githubusercontent.com/assets/3382128/4511958/ca3e807e-4b3a-11e4-86db-e3b3bd904642.png)
![slfn_2](https://cloud.githubusercontent.com/assets/3382128/4511959/ca49063e-4b3a-11e4-9f29-79f99cc40af1.png)