> > > @Thomas > I still think the optimization problem is not feasible due to your data. > Have you tried balancing the dataset as I mentioned in your other question > regarding the > > MLPClassifier? > > > Hi Piotr,
I had tried all the balancing algorithms in the link that you stated, but the only one that really offered some improvement was the SMOTE over-sampling of positive observations. The original dataset contained 24 positive and 1230 negative but after SMOTE I doubled the positive to 48. Reduction of the negative observations led to poor predictions, at least using random forests. I haven't tried it with MLPClassifier yet though.
_______________________________________________ scikit-learn mailing list [email protected] https://mail.python.org/mailman/listinfo/scikit-learn
