[WIP] Sparse Target Dummy Classifier

- [x] Test sparse with all four strategies 
- [x] Fit with sparse target
- [x] Predict sparse target
- [ ] 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
- [ ] Test random sampling function with simulation
- [ ] Uniques/class distribution function for multilabel-multioutput (share with sprs knn)
I believe I understand how this works, but I don't think it allows for random sampling with no replacement.