Super—thanks for the advice, Mike
From: Pkg-ExpPsy-PyMVPA [mailto:pkg-exppsy-pymvpa-bounces+michael.browning=psych.ox.ac...@lists.alioth.debian.org] On Behalf Of Richard Dinga Sent: 13 August 2015 15:31 To: pkg-exppsy-pymvpa@lists.alioth.debian.org Subject: Re: [pymvpa] Altering the weights of classes in binary SVM classifier > My sample is not balanced (there happens to have been 22 responders > and 13 non-responders) and is not particularly large. I would like, > if possible, to use all the data and adjust the classifier to the > unbalanced set rather than selecting a subset of the responders. You don't have to downsample, you can upsample by repeating balanced sampling n times, therefore all your data would be used. There is a balancer feature for it in pymvpa. > I've seen recommendations for SVMs in unbalanced data suggesting that > the weights of the outcome can be adjusted to reflect the sample size > (essentially the weights of each class can be set as 1/(total number > in > class)). Yes, you can also move a decision threshold for some classifiers that outputs probability, so you will not predict class A if the prob of A is > 0.5 but if the prob of A > is number of A / number of total. I know you can do this with gaussian process clf, but i don't know about others > I've tried to do this in pyMVPA using the following code: > wts=[ 1/numnonresp, 1/numresp] > wts_labels=[0,1] > clf = LinearCSVMC(weight=wts, weight_label=wts_labels) > I then embed the classifier in a crossvalidation call which includes > a > feature selector. > The code runs without error but the performance of the classifier > does not alter (at all) regardless of the weights I use (e.g. using > weights of [0 100000000000] or whatever. I'm concerned that I have > not set this up correctly, and that the weights are not being > incorporated into the SVM. It didn't work for me either. You can try implementation from scikit-learn with pymvpa sklearn adaptor. There you can just put class_weight to auto and it should adjust them proportionally to class frequencies automatically Best wishes, Richard
_______________________________________________ Pkg-ExpPsy-PyMVPA mailing list Pkg-ExpPsy-PyMVPA@lists.alioth.debian.org http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
