Chandan Singh

That is correct, we are working on this but for now if you want to use categorical variables you'll have to first one-hot encode them.

Good point! You are correct my above comment was about categorial feature variables which an be used with one-hot encoding. Most of the models here only support binary classification (see...

We do plan to add it although it may not be for another month - RuleFit, SLIM, FIGS, and HSTree (among others) should easily support multi-class, but we haven't been...

Hi Nick, you're right this is currently not supported (the shrink function is written only for univariate regression/binary classification and misbehaves with multiple classes). It's a pretty straightforward extension though...

@Innixma should work now :)

Thanks for the really helpful comments Nick, very nice! @OmerRonen do you think you can handle the comments? Let me know if you're busy and I can take a crack.

Thanks for pointing this out - it's a good idea and we'll add it soon! In the meantime, you can set the `max_rules` parameter in the `FIGSRegressor` to some reasonable...

Ah thank you for pointing this out - indeed we will fix it on our end. The issue is that currently the FIGSRegressor `predict` function expects a numpy array not...

Hi Austin, thanks for the link! ftrees would be a very nice add to the package :) We are a bit busy at the moment trying to integrate this package...

+1