fishermain.m

fisher算法在多类情况下的matlab实现

clear;
load data_for_PR;
i=1;
data=data(1:12,1:176);% 取CCV特征
while i~=size(data,1)
    if data(i,:)==0
        data(i,:)=[];
    else
        i=i+1;
    end
end
data=data';
label=label';
data=scale(data);%缩放到[0,1];
data=data;
train_data=[];
test_data=[];
train_label=[];
test_label=[];
[sample_num,feature_num]=size(data);
j=0;
k=0;
for i=1:sample_num
    if mod(i,4)==0
        j=j+1;
        test_data(j,:)=data(i,:);
        test_label(j,:)=label(i,:);        
    else k=k+1;
        train_data(k,:)=data(i,:);
        train_label(k,:)=label(i,:);        
    end
end
[Accuracy,predicted]=multiclassfisher(train_data,test_data,train_label,test_label);
fprintf('预测成功率为%f\n',Accuracy);