> The Spider Objects

>            LOOM object

>        A=LOOM(H) returns a loom object initialized with hyperparameters H.

>        Hyperparameters, and their defaults
>         R=1                  -- the soft margin parameter K=K-R*diag(diag(K))
>         A=0.001;             -- additional regularization on alphas, A*||alpha||_1
>         ridge=1e-12;         -- a ridge on the kernel
>         balanced_ridge=0     -- for unbalanced data
>         child=kernel         -- the kernel is stored as a member called "child"

>        Model
>         alpha                -- the weights
>         b0                   -- the threshold
>         Xsv                  -- the Support Vectors

>        Methods:
>         train, test

> | Reference : Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers

> | Author : Theodoros Evgeniou ,Massimiliano Pontil , André Elisseeff

> | Link : http://portal.acm.org/citation.cfm?id=974025.974029&dl=GUIDE&dl=GUIDE