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

Please add an interpretation of the results here: in particular we should highlight the fact that if the raw GNB calibration curve is above the diagonal it's because the classification is imbalanced and led the GNB model to classify many positive example as negative (bad precision).

It would also be interesting to compute and print `classification_report` or at least the precision and recall (and f1-score) for the positive class for each model (calibrated or not) and highlight the fact that calibration can fix the bad handling of class imbalance by the GNB model.

It's important that the text of the example both presents the experiment run in the example and critically analyze the obtained results.

In particular it can be seen that the logistic regression model is well calibrated by default as it curve is very close to the diagonal.