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
I am happy that it helps you. :-)

> If I make _recursive_lsqr as a function wouldn't I need to pass many parameters?

In my opinion, it would have the advantage to make everything explicit. Furthermore, you could easily test and check the correctness of this solver (no state involved). Lastly, it might highlight an appropriate interface for more solver (sgd?).

Your suggestion looks good. I am eager to have a look at it. Thanks fewer methods means fewer overhead for my brain. ;-)