sklearn logistic regression with unbalanced classes

Question

I\'m solving a classification problem with sklearn\'s logistic regression in python.

My problem is a general/generic one. I have a dataset with two classes/result (posi

Answer 1

Have you tried to pass to your class_weight="auto" classifier? Not all classifiers in sklearn support this, but some do. Check the docstrings.

Also you can rebalance your dataset by randomly dropping negative examples and / or over-sampling positive examples (+ potentially adding some slight gaussian feature noise).