PaulWestenthanner

One of the big advantages of this library is a rather common interface to all the different encoders (e.g. for handling missing values or unknowns). It makes a lot of...

Hi @glevv I'm sorry, I haven't seen you've been working on this. Why did you close the Pull Request after only one day? I think it would be a useful...

Ok nice! Do you want to continue working on it? Otherwise I might look into it in March/April

Hi Julia, great! Looking forward to your contribution :)

Hi Julia, thanks for all the work you've put into this. I really like your suggestions: 1. The CategoryEncoders library aims to handle missing values. Especially for target-encoding-based encoders this...

I just added sklearn >= 1.0 to the requirements

Hi Valdimir, Contributions are always welcome. There are a couple of issues tagged with 'good first issue'. Feel free to work on one of them (or come up with other...

A similar discussion has taken place already in #227 and was considered off topic and too broad which I also agree with. So I'm closing this issue

looking at this again with issue #402 in mind I'd suggest changing this https://github.com/scikit-learn-contrib/category_encoders/blob/f6349a140c8477b612a63c7d8f5cfe21139f5989/category_encoders/hashing.py#L301 to `val = ''.join(x.values)` and then hash the combined string from all columns. and this needs...

never mind my suggestion. You're right of course. So basically our documentation is just wrong since it suggests that n-components is the number of bits. I'll close this issue again