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
Dumb question: In [`kernel_metrics`](https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/metrics/pairwise.py#L1122), we have other kernels (for example additive_chi2). Is there reasons not to support it?