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
This could be a possibility.

Would it make sense to keep the one-liner version (`print("Training mean square error = %f" % mean_squared_error(y, self._predict(X)))`) as it is the objective function of the ELM algorithm?