I suspect that there might be something wrong in the code/how the data is handled.
If you 30% accuracy then that would mean that you will get 70% if you use a simple rule to predict the "other class" after your classifier. This is a sign that something is not right in data handling/evaluation. Best On Mon, Nov 26, 2018 at 1:27 PM Raúl Hernández <r...@lafuentelab.org> wrote: > No, it is balanced. It has the same number of observations for each class. > > On Mon, Nov 26, 2018 at 12:52 PM Kaustubh Patil <kaustubh.pa...@gmail.com> > wrote: > >> Just for clarification. >> >> Is that data imbalanced, i.e. many more observations from one class? >> >> Best, >> Kaustubh >> >> On Mon, Nov 26, 2018 at 12:50 PM Raúl Hernández <r...@lafuentelab.org> >> wrote: >> >>> Dear PyMVPA community, >>> >>> I'm doing classification in ROI's, I'm performing a simple 2 way >>> classification using LSVM, and a leave-one-run-out cross-validation on 4 >>> acquisitions. On some ROI's, I get a good accuracy for the number of >>> participants (60%), but in others I get consistently bad accuracy (30%). To >>> test whether the performance is above chance, I use a one sample t test (I >>> know that it is not the best test for this type of data, I just use it as >>> quick overview). When I test the bad accuracies, those are also significant. >>> >>> What does it mean a consistently bad accuracy? >>> >>> Regards, >>> >>> Raul >>> _______________________________________________ >>> Pkg-ExpPsy-PyMVPA mailing list >>> Pkg-ExpPsy-PyMVPA@alioth-lists.debian.net >>> >>> https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa >> >> _______________________________________________ >> Pkg-ExpPsy-PyMVPA mailing list >> Pkg-ExpPsy-PyMVPA@alioth-lists.debian.net >> https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > Pkg-ExpPsy-PyMVPA@alioth-lists.debian.net > https://alioth-lists.debian.net/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
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