[WIP] Generative Classification

This PR adds a simple meta-estimator which accepts any generative model (normal approximation, ``GMM``, ``KDE``, etc.) and uses it to construct a generative Bayesian classifier.

Todo:
- [ ] code documentation
- [ ] narrative docs
- [ ] testing
- [ ] examples

One question is, if this is merged, how should it be combined with the ``sklearn.naive_bayes`` tools?  In a sense, this is simply a generalization of those (e.g. the classifier ``GenerativeBayes('norm_approx')`` is effectively identical to the ``GaussianNB()`` classifier).

Currently, this is just in proof-of-concept form, and I'd love to hear thoughts or suggestions!