Anthony Blaom, PhD

@bensadeghi Thanks for that quick response. In this case, then, the claim that the package provides "support for mixed categorical and numerical data" is indeed misleading. You only support ordered...

@bensadeghi Thanks for that. However, it seems the feature requirements stated for classifiers and regressor are now different: For classification we have "support for ordered features (encoded as Reals or...

I don't see any harm in this enhancement, apart from a mild complication in the codebase. Anyone else have objections? @sanderbboisen Would you be willing to add a test of...

I am happy with this now. I suspect this smaller PR may create a few merge conflicts for the more complicated #166, so let's wait for: - [x] #166 is...

@sanderbboisen Would you now be happy to rebase your PR?

@tecosaur Thanks indeed for this. I expect we will have some merge conflicts with the large PR #166 which is almost done. Let's rebase this PR after that and then...

Very cool! I wonder what the best way to integrate this contribution might be. Be great for MLJ users to be able to do this (without adding Makie as dependency...

> x.encoding contains the class label information and not the features. Yes, of course you right 👍🏾 . Perhaps we could get the MLJ interface to expose the feature names...

@roland-KA Very nice summary of the issues and best options. I agree that while @Rahulub3r code is a lovely bit of work, a more generic solution is preferred (1 or...

I agree this looks nice. However, as it is specific to DecisionTree.jl trees, I suggest a PR either to DecisionTree.jl and/or MLJDecisionTreeInterface.jl. The MLJDecisionTreeInterface version could include original feature names....