> The Spider Objects

>       RSC_l0 reduced set selection

>        a = rss_l0(alg,hyper)
>        generates a rss object, using the l0 norm

>        hyperparameters:
>        child=svm         algorithm worked on
>        reoptimize_b=1    recalculate the threshold b0
>        a.lambda=0        regularizer for selection
>                          set to -1 for automatic selection
>        reoptimize=1
>        tolerance=0.05    tolerance in ||w-w*||^2
>        max_loops=40      limit on loops

>        model:
>        alpha         new alphas for rs-vectors
>        Xsv           rs vectors
>        b0            the threshold
>        w2            final value of ||w*-w^2||^2, set to -1 to calculate

>        stats:
>        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

>        methods:
>        train         constructs a reduced set, returns trained rs-machine
>        test          tests new rs-machine on supplied data

>        example:
>        d=gen(toy2d('2circles','l=100'));
>        [r,a]=train(svm({kernel('rbf',1),'C=10000','alpha_cutoff=1e-2'}),d);
>        [r,a2]=train(rss_l0(a,'lambda=1e-2'),d);
>        test(a2,d,loss)

>        author: goekhan bakir, jason weston
>        reference: fast binary and multi-output rss, 2004