Test the performance of behavior recognition using cross validation.
Training occurs on all but (n-1) of the sets and testing on the remaining one, giving a
total of (n) training/testing scenarios. One simplification is used here: clustering is
done only once, using all of the data. When reporting final results, clustering needs
to be done each time separately, as in recog_test.
Parameters for clustering and classification can be specified inside this file.
INPUTS
DATASETS - array of structs, should have the fields:
.IDX - length N vector of clip types
.desc - length N cell vector of cuboid descriptors
.ncilps - N: number of clips
k - number of clusters
nreps - number of repetitions
OUTPUTS
ER - error - averaged over nreps
CM - confusion matrix - averaged over nreps
See also RECOGNITION_DEMO, RECOG_TEST, NFOLDXVAL, RECOG_CLUSTER, RECOG_CLIPSDESC