Code covered by the BSD License  

Highlights from
Discriminant Analysis via Support Vectors

image thumbnail
from Discriminant Analysis via Support Vectors by Suicheng Gu
Discriminant Analysis via Support Vectors codes

oneoutsvnn(fea,gnd,k)
function total = oneoutsvnn(fea,gnd,k)
% total : Number of wrong classification samples
[N,d] = size(fea);
total = 0;
dd = zeros(N-1,1);
for num = 1:N;
    tri = zeros(N-1,d);
    tei = fea(num,:)/100;
    tel = gnd(num);
    tri(1:num-1,:) = fea(1:num-1,:)/100;
    trl(1:num-1,:) = gnd(1:num-1,:);
    tri(num:N-1,:) = fea(num+1:N,:)/100;
    trl(num:N-1,:) = gnd(num+1:N,:);
    V = SVDA(tri,trl,k);
    tri = tri*V;
    tei = tei*V;
    for i = 1:N-1;
        dd(i) = (tri(i,:)-tei)*(tri(i,:)-tei)';
    end;
    [p,index] = min(dd);
    if tel ~= trl(index);
        total = total+1;
    end;
end;

Contact us at files@mathworks.com