SPIDER The Spider Objects

RSC_MP reduced set selection

   a = rss_mp(alg,hyper)
   generates a rss object, using the matching pursuit selection method
   child=svm         algorithm worked on
   max_loops=1e5     maximum number of basis functions
   tolerance=1e-5    tolerated loss in ||w-w*||^2
   backfit=1         backfit on every nth iteration
   backfit_at_start=100  always backfit for first e.g. 100 iterations 
   dont_revisit=1    dont return to old basis function optimization, always get new one
   reoptimize_b=1    recalculate the threshold b0
   alpha_cutoff=0    throw away svs with abs(alpha)   bal_w=0           treat multiple w's as equal by normalizing by length
   optimizer='iterative' iterative update of matrix inverse
   alpha         new alphas for rs-vectors
   Xsv           rs vectors
   b0            the threshold
   w2=0          final value of ||w-w*||^2 
   res=[]        results on a separate test set
   dtst=[]       separate test set  
   test_on=0     iterations to test on
   train         constructs a reduced set, returns trained rs-machine
   test          tests new rs-machine on supplied data
   author: goekhan bakir, jason weston
   reference: fast binary and multi-output rss, 2004