multiclassfisher.m

fisher算法在多类情况下的matlab实现

function [accuracy,predicted]=multiclassfisher(train_data,test_data,train_label,test_label)
%UNTITLED1 Summary of this function goes here
%   Detailed explanation goes here
class_num=length(unique(train_label));%多少类
mean_by_class=zeros(class_num,size(train_data,2));%各类样本的均值
sum_by_class=zeros(class_num,size(train_data,2));%各类样本的总和
every_class_num=zeros(1,class_num);%每类包含的样本数
for i=1:size(train_data,1)
    every_class_num(train_label(i))=every_class_num(train_label(i))+1;
    sum_by_class(train_label(i),:)=sum_by_class(train_label(i),:)+train_data(i,:); 
end
for j=1:class_num
   mean_by_class(j,:)=sum_by_class(j,:)/every_class_num(1,j);
end
Si=cell(1,class_num);
for i=1:class_num
    Si{i}=zeros(size(train_data,2));
end
for i=1:size(train_data,1)
    Si{1,train_label(i)}=Si{1,train_label(i)}+(train_data(i,:)-mean_by_class(train_label(i)))'*(train_data(i,:)-mean_by_class(train_label(i)));
end
W=cell(class_num);%vector for projection
Y=cell(class_num);%threshold
for m=1:class_num
    for n=1:class_num
        if m~=n
        W{m,n}=inv(Si{1,m}+Si{1,n})*(mean_by_class(m,:)-mean_by_class(n,:))';    
        end
    end
end
for m=1:class_num
    for n=1:class_num
        if m~=n
        Y{m,n}=W{m,n}'*(sum_by_class(m,:)+sum_by_class(n,:))'/(every_class_num(m)+every_class_num(n));    
        end
    end
end
predicted=zeros(length(test_label),class_num);%预测向量
for k=1:length(test_label)
    for m=1:class_num
        for n=1:class_num
            if m~=n
                J=test_data(k,:)*W{m,n};
                if J>Y{m,n}
                    predicted(k,m)=predicted(k,m)+1;
                else
                    predicted(k,n)=predicted(k,n)+1;
                end
            end
        end
    end
end
temp=zeros(size(test_label));
for i=1:length(test_label)
    for j=1:class_num
        if predicted(i,j)==max(predicted(i,:));
            temp(i)=j;
        end
    end
end
predicted=temp;
count=0;
for k=1:length(test_label)
    if predicted(k)==test_label(k)
        count=count+1;
    end
end
accuracy=count/length(test_label);