[WIP] Sparse Target Dummy Classifier

- [x] Test a sparse multioutput case
- [x] Fit with sparse target
- [ ] Predict sparse target
It looks this could be improved by working directly on y.data of the csr matrix. I would do

1. convert to csc
2. eliminate zeros
3. count the number of zeros of the column through indptr
4. compute the unique set of non zero classes and get the inverse
5. Add the zero class in classes if the columns is not dense
6. perform a bincount on the classes and use the minlength paramter
7. compute the class_prior