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
I tried using `self.score(X, y)` function but it requires `y` in its original form :(.
Maybe I could keep `y` as is and initialize a capitalized letter, `Y`,  to be the transformed version of `y`, then below the `verbose` condition, I call 
```python
print("Training score = %f" % self.score(X, y))
```
?