Classifiers

- Classifiers binary, single-label, OneVsRest or MultiOutput:
    - LR
    - LinearSVC (?)

- Classifiers natively multi-label:
    - from scikit-multilearn (x11)
    -

Protocols:
    - NPP
    - APP (for each class)



Things to test:
- MultiChain for classification, MultiChain for regression...
- Reimplement stacking with sklearn.ensemble.StackingClassifier? No parece facil.

- Independent classifiers + independent quantifiers
- Stacking + independent quantifiers
- ClassifierChain + independent quantifiers
- Independent quantifiers + cross-class regression (independent?)
- Stacking + cross-class regression
- ClassifierChain + cross-class regression
- Covariates (Means, CovMatrix from samples) + multioutput regression?
- Covariates concatented with quantifiers predictions + cross-class regression?

- Model Selection for specific protocols?

TODO:
- decide methods
    - decide classifiers binary
    - decide classifiers multi-label
    - decide quantifiers naive
    - decide quantifiers multi-label
- decide datasets