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erdogant / hgboost

hgboost is a python package for hyper-parameter optimization for xgboost, catboost or lightboost using cross-validation, and evaluating the results on an independent validation set. hgboost can be applied for classification and regression tasks.
http://erdogant.github.io/hgboost
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TypeError: LGBMRegressor.fit() got an unexpected keyword argument 'early_stopping_rounds' #16

Open juanramonua opened 11 months ago

juanramonua commented 11 months ago

First of all, thank you for the development of this Sw that allows in an easy way to find the optimal parameters for gradient descent algorithms with boosting.

It seems to me that they have updated the LGBM version and now 4.0.x is available. I am using Google Colab, and installing the package, both by pypi and directly from Github shows the error in the title.

I hope it can be easily fixed. Best regards.

erdogant commented 11 months ago

I created a fix where I updated the input parameter for the latest version of lightboost. Can you update to the latest version and check whether this works again?

pip install -U hgboost