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
run pyflakes:


```
sklearn/neural_network/extreme_learning_machines.py:10 'linalg' imported but unused
sklearn/neural_network/extreme_learning_machines.py:11
  'identity' imported but unused
sklearn/neural_network/extreme_learning_machines.py:21
  redefinition of unused 'check_random_state' from line 20
sklearn/neural_network/extreme_learning_machines.py:21
  redefinition of unused 'atleast2d_or_csr' from line 20
```