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
Please rename `H` and `A` as `activations`. Also rename `_activation_func` to `_inplace_activation` and do:

```python
activations = safe_sparse_dot(X, self.coef_hidden_)
activations += self.intercept_hidden_
self._inplace_activation(activations)
```

to make it explicit that there is no memory copy besides the initial allocation of the `safe_sparse_dot` function.