I think a correlation classifier/method was used in Haxby's et al 2001 work, and it gave high classification accuracy using the averages. One might argue that, although not sure about this, assigning a volume/exemplar to a single label/condition is problematic, thus, averaging is a good option.
Using a correlation-based classifier on exemplars/volumes would give less accuracy than the using the averages, but other powerful classifiers, e.g. SVMs, LR, ANN, RIDGE-LR will do well. -Rawi > On Thursday, January 23, 2014 8:06 PM, J.A. Etzel <[email protected]> > wrote: > > I also agree, and will "toss in" a few more ideas: > >>> But forming decisions boundaries over features is exactly what a >>> classifier is meant to do, so why not just throw all these >>> different exemplars into the mix, and let the classifier figure out >>> its own notion of prototypicality? > I think because of power, particularly the lack of it. Our datasets are > usually massively out of balance (way more dimensions than examples), > making learning quite difficult. It often just isn't possible to further > subdivide the data to let the classifier learn the exemplars as well. > >>> And if you’re going to pre-classify, why pick the average >>> response? Why not take some kind of lower-dimensional input; the >>> first several eigenvectors or something, or something else? > Probably the most common technique other than averaging is creating > "parameter estimate images": taking the beta weights that result from > fitting a linear model to the inputs, convolved with a hemodynamic > response function. This can be done in programs such as SPM, and is a > bit closer to the first level analyses done for mass-univariate analysis. > >> It seems weird to average the regressor weights, but maybe it >> shouldn't. Is that something that's done, or is the averaging > process >> only used with raw voxel activity? > It does seem a bit weird, but I've done it. It feels "cleaner" to > generate a single set of parameter estimates than to generate one per > example (or run) then average, but I don't know if it is actually > mathematically different. > > Jo > > > -- > Joset A. Etzel, Ph.D. > Research Analyst > Cognitive Control & Psychopathology Lab > Washington University in St. Louis > http://mvpa.blogspot.com/ > > _______________________________________________ > Pkg-ExpPsy-PyMVPA mailing list > [email protected] > http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa > _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
