WIP : Isotonic calibration

calibration module with platt and Isotonic calibration.

A few issues :

- [x]  nice calibration plots
- [x]  add tests for metrics
- [x]  add narrative doc

This is actually not checked by the `_check_and_normalize` helper. Actually it should accept arbitrary labels such as `[-1, 1]` or `['spam', 'ham']` as another classification metrics and make it explicit which label is the positive labels with an additional `pos_label` parameter as done for other binary classification metrics such as `f1_score` for instance.

Please add tests for this.