[MRG] Sparse Target Dummy Classifier

- [x] Test sparse with all four strategies 
- [x] Fit with sparse target
- [x] Predict sparse target
- [x] ~~Simplify (skip steps) when constant strategy is used~~
- [x] Clean up redundancies of indicies, data, indptr in predict
- [x] Clean up conditional redundancies in fit 
- [x] Random sampling function outputs sparse column
- [x] Test random sampling function ~~with simulation~~
- [x] Uniques/class distribution function for multilabel-multioutput (share with sprs knn)
- [x] Always use dense predict with uniform case, and throw a sparse efficiency warning.
This attribute is not documented.

By the way, I would rename`sparse_target_input_` to  `sparse_output_`. This would be consistent with LabelBinarizer.