Hey! One simple solution that often works wonders is to set the class_weight parameter of a classifier (if available) to 'auto' [1].
If you have enough data, it often also makes sense to balance the data beforehand. [1] http://scikit-learn.org/dev/modules/svm.html#unbalanced-problems Am 25.02.2013 14:02, schrieb Maor Hornstein: > I'm using scikit-learn in my Python program in order to perform some > machine-learning operations. The problem is that my data-set has severe > imbalance issues. > > Does anyone know a solution for imbalance in scikit-learn or in python > in general? > > > Thanks :) > > > > ------------------------------------------------------------------------------ > Everyone hates slow websites. So do we. > Make your web apps faster with AppDynamics > Download AppDynamics Lite for free today: > http://p.sf.net/sfu/appdyn_d2d_feb > > > > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Everyone hates slow websites. So do we. Make your web apps faster with AppDynamics Download AppDynamics Lite for free today: http://p.sf.net/sfu/appdyn_d2d_feb _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
