gininorm.m

the matlab code of ginisvm - an svm implementation good at probability regression.

function [rateval,znorm] = ginitest(inpvec,gamma);
%------------------------------------------------
% This function implements the gini normalization
% procedure by finding a threshold using the
% reverse water-filling procedure.
%
% inpvec -> Unnormalized inputs.
% gamma  -> Normalization Factor.
% rateval-> Probability vector.
% znorm  -> threshold factor.
%------------------------------------------------

[L,M] = size(inpvec);

rateval = zeros(1,M);
znorm = 0;

if gamma > 0,
   [fthd,ind] = sort(inpvec);
   target = gamma;
   zt = 0;
   curr = M;
   while zt < target & curr >= 2,
       zt = sum(fthd(curr:M) - fthd(curr-1));
       curr = curr - 1;
   end;
   if curr == 1,
       if zt < target,
       % Means we have to include the total classes
            znorm = 1/M*(sum(fthd(curr:M)) - target);
            for class = curr:M,
                  rateval(ind(class)) = ((inpvec(ind(class)) - znorm));
            end;
        else
            znorm = 1/(M-1)*(sum(fthd(2:M)) - target);
            for class = curr+1:M,
               rateval(ind(class)) = ((inpvec(ind(class)) - znorm));
            end;
        end;
    else
        znorm = 1/(M-curr)*(sum(fthd(curr+1:M)) - target);
        for class = curr+1:M,
            rateval(ind(class)) = ((inpvec(ind(class)) - znorm));
        end;
    end;
end;