Data type specification and checking

[robertness]

Is your feature request related to a problem? Please describe.
The type and domain of the variables in the data should be a first class citizen

Describe the solution you'd like

• Way to explicitly specify type (and possibly range) of variables in the context variable
• Informative errors when a method doesn't work with a provided data type

Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.

Additional context
This is also related to making assumptions first class citizens.

[adam2392]

I think we can follow a similar approach to scikit-learn and assume continuous by default and allow users to pass in a categorical mask (e.g. https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html).

Idk if range of variables is important tho?

Then, we could have private attributes for each method _supports_categorical, _supports_mixed, _supports_continuous that is checked during fit(...)