[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
If `sample_weight` is not `None`,  one should not call `compute_sample_weight` but just use the provided weights. Please also add some tests on a toy data to check that sample_weight can be used to ignore some samples from the training set, as done here: https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/ensemble/tests/test_gradient_boosting.py#L978