In case y'all didn't see this... P
---------- Forwarded message ---------- From: Sam Gershman <[EMAIL PROTECTED]> Date: Tue, Sep 30, 2008 at 7:43 PM Subject: new feature selection algorithm To: [EMAIL PROTECTED] Hi all, Some people might be interested in this: http://www.pnas.org/content/105/39/14790.full It just came out in PNAS. The paper describes an algorithm for feature selection called "higher criticism." It is designed for a particular classification setting dubbed "rare/weak": where the fraction of useful features is small and the useful features are each too weak to be useful on their own. The idea is to look at the distribution of feature statistics and use the deviation from an expected null distribution to set the feature selection threshold. Although based in frequentist statistics and therefore fundamentally flawed, it shows some interesting behavior that could be highly advantageous to MVPA applied to fMRI. Apart from its explicit designation for the R/W setting (which is obviously apt for fMRI), it doesn't require tuning by cross-validation and the threshold has low variance (which might be good when looking for consistent feature sets). Sam _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/mailman/listinfo/pkg-exppsy-pymvpa
