Sign Up to our social questions and Answers Engine to ask questions, answer people’s questions, and connect with other people.
Login to our social questions & Answers Engine to ask questions answer people’s questions & connect with other people.
Lost your password? Please enter your email address. You will receive a link and will create a new password via email.
Please briefly explain why you feel this question should be reported.
Please briefly explain why you feel this answer should be reported.
Please briefly explain why you feel this user should be reported.
With scikit-learn, is there a way to pass additional parameters to the fit method of a classifier, when using cross_val_score? For instance, how would you specify the sample_weight or class_prior, for a MultinomialNB classifier:
I did as suggested, and implemented the feature myself, which has been added to the 0.13 release, as
fit_params:https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.cross_val_score.html