> The Spider Objects

>       RSC_FP reduced set construction - fixpoint method

>        a = rsc_fp(alg,hyper)
>        generates a rsc object, using the fixpoint method

>        hyperparameters:
>        child=svm     algorithm worked on
>        rsv=.5        if rsv e [0,1): #rsv = #sv * rsv
>                      if rsv > 1: #rsv
>        max_it=10     maximum of iterations per class
>        eps=1e-5      epsilon

>        model:
>        alpha         new alphas for rs-vectors
>        Xsv           rs vectors

>        stats:
>        w2=0          final value of ||w-w*||^2
>        dw=0          total decrease in ||w-w*||^2

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

>        remark:
>        supports only rbf-kernels!

>        example:
>        d=gen(toy2d('2circles','l=100'));
>        [r,a]=train(svm({kernel('rbf',1),'C=10000','alpha_cutoff=1e-2'}),d);
>        [r,a2]=train(rsc_fp(a,'rsv=.9'),d);
>        test(a2,d,loss)

>        author: b. schoelkopf et al.
>        reference: learning with kernels, chpt. 18