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Alex Rivera
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Is it possible to perform a GridSearchCV (to get the best SVM's C) and yet specify the sample_weight with scikit-learn? Here's my code and the error I'm confronted to: gs = GridSearchCV( svm.SVC(C=1), [{ 'kernel': ['linear'], 'C': [.1, 1, 10], 'probability': [True], 'sample_weight': sw_train, }] ) gs.fit(Xtrain, ytrain) >> ValueError: Invalid parameter sample_weight for estimator SVC Edit: I solved the issue by getting the latest scikit-learn version and using the following: gs.fit(Xtrain, ytrain, fit_params={'sample_weight': sw_train})
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