On Mon, 15 Apr 2013, Paul Robinson wrote: > Hi, Yaroslav.
> As follows: > >>> print fds.summary() > Dataset: 39x172800@float32, <sa: > chunks,targets,time_coords,time_indices>, <fa: voxel_indices>, <a: > imghdr,imgtype,mapper,voxel_dim,voxel_eldim> > stats: mean=-0.00263811 std=0.566497 var=0.320918 min=-5.24132 max=5.29731 > No details due to large number of targets or chunks. Increase maxc and > maxt if desired > Summary for targets across chunks > targets mean std min max #chunks > Control 0.513 0.5 0 1 20 > Patient 0.487 0.5 0 1 19 I suspect that you have placed each sample into a unique chunk (where they could actually rightfully belong since this is different subjects). Then with N-Fold partitioning you are pretty much doing leave-1-out. Hence your errors would be either 0 or 1 since you have only 1 sample you cross-validate into. print cvte.ca.stats should give you a better "picture" but mention that you have only few samples, and lots of features, and disbalance between conditions, so classifier might just go for the one with more samples to reduce error etc... > Sequence statistics for 39 entries from set ['Control', 'Patient'] > Counter-balance table for orders up to 2: > Targets/Order O1 | O2 | > Control: 19 1 | 18 2 | > Patient: 0 18 | 0 17 | > Correlations: min=-0.95 max=0.9 mean=-0.026 sum(abs)=19 this is irrelevant here since this is independent samples -- Yaroslav O. Halchenko http://neuro.debian.net http://www.pymvpa.org http://www.fail2ban.org Senior Research Associate, Psychological and Brain Sciences Dept. Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
