LGBMregressor 的 BayesSearchCV：如何在训练和 CV 评分中对样本进行加权？

Question

While optimizing LightGBM hyperparameters, I'd like to individually weight samples during both training and CV scoring. From the BayesSearchCV docs , it seems that a way to do that could be to insert a LGBMregressor sample_weight key into the BayesSearchCV fit_params option. But this is not clear because both BayesSearchCV and LGBMregressor have fit methods.

To which fit method is the BayesSearchCV fit_params going? And is using fit_params really the way to weight samples during both training and CV scoring?

Answer 1

Based on the documentation I believe fit_params is passed as an argument upon BayesSearchCV() instantiation, not when the.fit() method is called.