I am wondering if there is something similar in Julia to Python’s Catboost, i.e. a gradient boosted determinant model that allows for categorical and numeric data?
I found a Catboost.jl package, but it is reliant on mini-conda and my virtual environment won’t allow for this - and I would like a 100% Julia solution. I was also interested in any learning to rank (LTR) models such as LightGBM ranker - julia has a LightGBM but they haven’t imported the ranking feature for some reason?
The one package that got close to this is JLBoost.jl but is deprecated
I would be open to hearing about other packages / models that could achieve these as well.