Added sample weight support to confusion matrix.

Added a sample_weight parameter inside confusion_matrix which
will be used to build the confusion matrix. If not present, it
will default to np.ones() of size equal to the number of samples.
Tests were created in test_classification.py instead of
test_common.py.
I'd rather not have this hard-coded. More precisely, we can use:
```python
assert_array_almost_equal(cm,
                          .1 * confusion_matrix(y_true[:25], y_pred[:25]),
                          .2 * confusion_matrix(y_true[25:50], y_pred[25:50]),
                          .3 * confusion_matrix(y_true[50:], y_pred[50:]))
```