[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
Before the item on setting `C` I would put a item for `n_hidden` stating that larger number of nodes on the hidden layer make the ELM better able to capture complex interactions of input features and generally leads to better generalization as long as `C` and `weight_scale` can be tuned to avoid too much overfitting. However, larger values of `n_hidden` mean larger memory usage and longer training and prediction times.