Dear PyMVPA folks, Does the toolbox include an SVM version which returns the p-vals for each class, in a multiclass classification?
I know that libsvm returns probabilities, and I have been trying this via its Matlab interface. However, rather than returning a nice list of N p-vals for each of the N possible class-label assignments, it returns the p-vals for all of the pairwise two-class sub-classifications. In the case of 8 classes, there are 8*7/2 = 28 pairwise p-vals. Although there is almost certainly a simple way of transforming that collection of pairwise p-vals into a simple one-pval-per-class output, I don't know what it is. I sent a mail about that topic to the libsvm board, but it hasn't been answered yet: http://agbs.kyb.tuebingen.mpg.de/km/bb/showthread.php?tid=2104&pid=5606#pid5606 I know that PyMVPA includes wrappers around lots of different SVM implementations, so I was wondering if any of those implementations offers a more user-friendly outputting of multiclass p-values. In the mean-time, I can get p-values out of other multi-class classifiers, such as SMLR. But it would be nice to compare them against SVM p-values. Many thanks, Raj _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list Pkg-ExpPsy-PyMVPA@lists.alioth.debian.org http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa
