[MRG] Sample weights for gradient boosting

and piggy-packed ``'exponential'`` loss for binary classification (= AdaBoost).

I didn't implement sample weights for ``'lad'``, ``'huber'``, and ``'quantile'`` since it would require weighted median / percentiles. I will either raise a warning or exception in this case: what do you prefer?

cc @glouppe

TODO: ~~benchmark benchmark and some regression tests~~
Maybe this should be a `TypeError` and the error message should reflect the name of the concrete class of `self`. 

```python
raise TypeErrror('%s does not support predict_proba' % type(self).__name__)
```