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