Hello, You might achieve what you want by using sample weights when fitting your forest (See the 'sample_weight' parameter). There is also a 'balance_weights' method from the preprocessing module that basically generates sample weights for you, such that classes become balanced.
https://github.com/glouppe/scikit-learn/blob/master/sklearn/preprocessing.py#L1221 (This should appear in the reference, I'll fix that) Hope this helps, Gilles On 8 February 2013 00:44, Manish Amde <manish...@gmail.com> wrote: > Fellow sklearners, > > I am working on a classification problem with an unbalanced data set and > have been successful using SVM classifiers with the class_weight option. > > I have also tried Random Forests and am getting a decent ROC performance but > I am hoping to get a performance improvement by using Weighted or Balanced > Random Forests as suggested in this paper. > http://www.stat.berkeley.edu/tech-reports/666.pdf > > I don't see any implementation of these options but I might be mistaken so I > wanted to ask the community. Also, I am willing to write code and contribute > back if this will be useful to other folks. > > I have also thought about balancing the data using up/down sampling the > minority/majority class (with or without replacement) and even SMOTE but > couldn't find those implementation in the scikit-learn library yet. The > modified Random Forests seem to outperform these methods according to the > paper, hence I am interested in trying those first. > > -Manish > > ------------------------------------------------------------------------------ > Free Next-Gen Firewall Hardware Offer > Buy your Sophos next-gen firewall before the end March 2013 > and get the hardware for free! Learn more. > http://p.sf.net/sfu/sophos-d2d-feb > _______________________________________________ > Scikit-learn-general mailing list > Scikit-learn-general@lists.sourceforge.net > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > ------------------------------------------------------------------------------ Free Next-Gen Firewall Hardware Offer Buy your Sophos next-gen firewall before the end March 2013 and get the hardware for free! Learn more. http://p.sf.net/sfu/sophos-d2d-feb _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
