test_set.asv

实现了fisher线性分类器的功能,源码使用matlab编程,通俗易懂

%%%%%%%%%%%%%%%%%%%%%%%%%% Testing %%%%%%%%%%%%%%%%%%%%%%%%%%
function E=Test_Set(TestSet,Training)
% 计算各类错误率e1,e2 和总错误率e
X=TestSet.X';
E=[0,0;0,0;0,0;0,0];
for num=1:4 %根据四种不同的y取值，进行分类
switch num
case 1,
    y=Training.y1;
case 2,
    y=Training.y2;
case 3,
    y=Training.y3;    
otherwise,
    y=Training.y4;    
end
for i=1:TestSet.n
    g=Training.W*X(:,i)-y;%判别函数
    if TestSet.CN(i)*g<0
        if TestSet.CN(i)==1
            E(num,1)=E(num,1)+1;%计算第1类被判错的错误率
        else
            E(num,2)=E(num,2)+1;%计算第1类被判错的错误率
        end
    end
end
e1=E(num,1)/TestSet.n1;
e2=E(num,2)/TestSet.n2;
e=(E(num,1)+E(num,2))/TestSet.n;
fprintf('方法%d:第1类错误率=%.2f%%,第2类错误率=%.2f%%,总错误率=%.2f%%\n',tk,e1*100,e2*100,e*100);
end
%%%%%%%%%%%%%%%%%%%%%%%% Testing End %%%%%%%%%%%%%%%%%%%%%%%%