> The Spider Objects

>       KVQ kpca object - Kernel Vector Quantization

>        A=KVQ(H) returns a kvq object initialized with hyperparameters H.

>        Hyperparameters, and their defaults
>         dist=1;          -- allowed point to point distortion.
>         child=linear         -- child stores the kernel. The kernel induced the used distance measure.
>         a.cutoff = 1./3.      -- cutoff value for importance values
>         a.return_indices = 0   -- return indices of points instead of samples.
>        Model
>        a.keep                -- kept data points -- store data points kept for model
>        a.alpha               -- importance factors
>        Methods:
>         train, test

>        Example:
>         d=gen(toy('n=2'));
>         [r,a]=train(kvq,d)
>         plot(a,d)

> | Reference : A kernel approach vor vector quantization with guaranteed distortion bounds

> | Author : M. Tipping, B. Schölkopf

> | Link : ftp://ftp.research.microsoft.com/users/mtipping/aistats01.ps.gz