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CatBoost has several parameters inside the fit method. One possible solution is to add a fit_params into the CatBoost function in FkLearn for increased flexibility.
This improvement would have to be done for both classification and regression.
This is important especially for CatBoost because the parameter that allows it to treat categorical features byitself is inside the fit method, and this is the main differential in this library.
Will this change a current behavior? How?
We would be able to configure the fit function using FkLearn.
Describe the feature and the current state.
fit
method. One possible solution is to add afit_params
into the CatBoost function in FkLearn for increased flexibility.This is important especially for CatBoost because the parameter that allows it to treat categorical features byitself is inside the
fit
method, and this is the main differential in this library.Will this change a current behavior? How?
We would be able to configure the fit function using FkLearn.
Additional Information
https://catboost.ai/docs/concepts/python-reference_catboost_fit.html
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