2012/12/4 Philipp Singer <kill...@gmail.com>: > > I use a linear SVM for learning my probabilities for the samples (I have > used grid search for determining the optimal paramters). Then I append > the additional features and do as suggested gradient boosting or extra > tree classifier. What do you mean by testing just a linear SVM? On my > new feature space?
Yes you could do that. > Btw, I just have 64 samples. I will try to append the probability > features using leave-one-out now. 64 samples is very small, even for a binary classification problem. I would strongly advise you to hand annotate new samples rather than trying to do any kind of complex modeling. -- Olivier http://twitter.com/ogrisel - http://github.com/ogrisel ------------------------------------------------------------------------------ LogMeIn Rescue: Anywhere, Anytime Remote support for IT. Free Trial Remotely access PCs and mobile devices and provide instant support Improve your efficiency, and focus on delivering more value-add services Discover what IT Professionals Know. Rescue delivers http://p.sf.net/sfu/logmein_12329d2d _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
