main1.asv

KNN最近邻分类器和预测器

load matlab.mat
K=9;
[train_set,test_set]=extract(train,0.2);
train_size=size(train_set,1)
test_size=size(test_set,1)
column=size(train_set,2)
correct_predict_num=0;
for i=1:test_size
    i
    for j=1:train_size;  
        dis(j)=distance(test_set(i,:),train_set(j,:));
    end
    [sorted_dis,index]=sort(dis);
    k=0;
    for m=1:9;
        if train_set(index(m),column)==1
            k=k+1;
        end
    end
    if k>4
        class=1;
    else
        class=0;
    end
    if class==test_set(i,column)
        correct_predict_num=correct_predict_num+1;
    end
end
correct_ratio=correct_predict_num/test_size