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
Thanks for highlighting this.

We don't need it because as soon as a sparse `X` is multiplied with `self.coef_hidden_` and added to `self.intercept_hidden_`, we get a dense `hidden_activations` which is the main component of `_HT_H_accumulated`.
So we will never have a sparse `_HT_H_accumulated`.