Fitting refactor : supplementary and categorical input

[ouakouak]

This first PR enables users to pass categorical features as attributes of the class, and also introduces support for supplementary variables in the fit method.

At the moment, users are essentially required to explicitly specify categorical features, as no automatic type detection has been implemented yet. We could consider adding such a feature later if needed.

Regarding supplementary variables, I have only added the necessary preprocessing step and passed them as arguments to super().fit.

Apart from that, the rest of the implementation remains unchanged, aside from some renaming of attributes. All previously implemented parts (except for the initial preprocessing before the call to super().fit) have simply been adapted to the new distinction between active attributes.
For now, supplementary variables are fitted but not fully integrated into the downstream computations.

Also added a small description to the class but can be modified or improved if needed.

[MaxHalford]

@ouakouak apologies for the delay reviewing!

[ouakouak]

No worries! I have an implementation that suits the one I need for my job at work. So no pressure on it, let's just build a consistent tool!

[MaxHalford]

@ouakouak I'm a bit lost with your PRs, so please remind me what needs reviewing and merging!

[ouakouak]

Ok so this branch needs to be merged (if you are done with rewiewing it). It was to require users to input categorical columns as a list in order to be an attribute of the class. It also enables to input supplementary variables in the fitting method (consistent with PCA's implementation).

[ouakouak]

I added descriptions to each PRs as well so it might help you to find yourself in the PRs. The PRS are this one, the #224 , the #225 and #226

[MaxHalford]

Ok clear, thanks. Could you rebase on main and figure out the broken tests?