Support different data types for optimization parameters

It would be nice to support different data types—e.g. int, float, bool, and maybe a categorical string—for the parameters over which we optimize. I am not sure what the syntax would look like, except for maybe a list of datatypes passed in that corresponds to the parameter bounds.

All three of these types could be handled the same way, with int being drawn uniformly from the integer interval specified, bool being drawn uniformly from {0, 1}, and categorical strings being mapped to a drawing from integer values [0, 1, ..., n_categories-1] or one-hot encoded as @PedroCardoso suggested below.

See [E. C. Garrido-Merchan and D. Hernandez-Lobato, 2017] for one approach.

[fmfn]

Interesting, the kernel change they propose wouldn’t be too hard to implement. My only concern is making the API more and more cumbersome by piling features. However this one is requested often enough to be worth considering.

[janwendt]

+1 I would like to use integers