I have a binary classificaiton problem with positive label proportion is very small, 1% at most of the cases. So, recall, precision and f score for the positive label is used to evauluate my classifiers.
However, the commom overfitting detecting method uses the metric MSE, accuracy to detect the situtaion. MSE, accuracy is useless in my situation.
So, is there any methods to detecting overfitting in the small proporation positive label binary classification problem?

  • $\begingroup$ Do you have enough positive label results to do cross validation? $\endgroup$ – russellpierce Dec 25 '15 at 16:03
  • $\begingroup$ I have 10,000,000+ samples, so 1% mean 100,000+ positive labels, I think it enougth $\endgroup$ – bourneli Dec 26 '15 at 8:46

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Browse other questions tagged or ask your own question.