How are you measuring your errors? If you are using the zero-one loss (accuracy score), you are taking in account only the binary decisions, and not a possible decision function. I have found that in the situation of unbalanced classes, it could be useful to threshold the decision function at a different value than 0, to maximize the left-out accuracy score.
Of course, that's an extra hyper-parameter, and I don't have a great way to set it. G ------------------------------------------------------------------------------ Want excitement? Manually upgrade your production database. When you want reliability, choose Perforce Perforce version control. Predictably reliable. http://pubads.g.doubleclick.net/gampad/clk?id=157508191&iu=/4140/ostg.clktrk _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general