> The Spider Objects

>       SVM + Local and Global Consistent Learner / Zhou

>         uses unlabeled data (Y=0) to solve classification problem.
>        a=lgcz(hyperParam)

>        Generates a lgcz object with given hyperparameters.

>          Hyperparameters (with defaults)
>          child=kernel         -- the kernel is stored as a member called "child"
>          propkern=kernel         -- the kernel which is used for propagation
>          ridge=1e-13          -- a ridge on the kernel
>           wide                --  the width of label propagation

>          Model
>           alpha               -- lagrangian multipliers
>           Xsv                 -- support vectors

>        Methods:
>         train, test, get_w

>        Example:
>        c1=[2,0];
>        c2=[-2,0];
>        X1=randn(50,2)+repmat(c1,50,1);
>        X2=randn(50,2)+repmat(c2,50,1);
>        Y= 0*[ones(50,1);-ones(50,1)];      kill all labels
>        Y(1)=1;
>        Y(end)=-1;              provide only two labelled points
>        d=data([X1;X2],Y);
>        clf;
>        hold on;
>        [r,a]=train(lgcz('ridge=1e-10'),d)
>        plot(a)
>        p=plot(d.X(1,1),d.X(1,2),'go');set(p,'MarkerFaceColor',[0,1,0]);
>        p=plot(d.X(end,1),d.X(end,2),'go');set(p,'MarkerFaceColor',[0,1,0]);
>        ['only green dots were labelled']

> | Reference : Learning with Local and Global Consistency

> | Author : Dengyong Zhou

> | Link : http://www.kyb.mpg.de/publication.html?user=zhou