> The Spider Objects

>            PLATT object

>        A=PLATT(C,H) returns a platt object initialized with hyperparameters H and
>                    based on algorithm C.
>        Converts a real valued margin producing pattern recognition
>        algorithm into a conditional probability estimator. It thus
>        requires a pattern recognition approach that can produce a real
>        valued output before thresholding, e.g SVMs. It achieves this
>        by finding the coefficients of a sigmoid by using cross validation.

>        Hyperparameters, and their defaults

>         child = svm          -- real valued margin algorithm to be used
>         folds = 3            -- number of cv folds

>        Model:
>         A                --
>         B                -- Parameters of the sigmoid: 1/(1+exp(A*f(x)+B)

>        Methods:
>         training, testing

>        Example:
>        [rr,a]=train(platt(svm),gen(toy))
>          rr.X  contains now the probability of being class 2
>          predictions
>        [sign(rr.X-0.5),rr.Y]

> | Reference : Probabilistic Outputs for Support Vector Likelihood Methods Machines and Comparisons to Regularized

> | Author : John Platt

> | Link : http://research.microsoft.com/users/jplatt/SVMprob.ps.gz