matlab实现的的knn分类器 有训练样本和测试样本
2016-08-23
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如何获取积分?
clear;
clc;
tic
load data.txt;
a=data(1:30,1:4);
aa=data(31:50,1:4);
b=data(51:80,1:4);
bb=data(81:100,1:4);
c=data(101:130,1:4);
cc=data(131:150,1:4);
train_sample=cat(1,a,b,c);%组成训练样本(90*4)
test_sample=cat(1,aa,bb,cc);%组成测试样本(60*4)
k=5;
cha=zeros(1,90);
sum=0;
[i,j]=size(train_sample);
[u,v]=size(test_sample);
for x=1:u
for y=1:i
result=sqrt((test_sample(x,1)-train_sample(y,1)).^2+(test_sample(x,2)-train_sample(y,2)).^2+(test_sample(x,3)-train_sample(y,3)).^2+(test_sample(x,4)-train_sample(y,4)).^2);
cha(1,y)=result;
end;
[z,ind]=sort(cha);
m1=0;
m2=0;
m3=0;
for n=1:k
if ind(1,n)<+30
 
clc;
tic
load data.txt;
a=data(1:30,1:4);
aa=data(31:50,1:4);
b=data(51:80,1:4);
bb=data(81:100,1:4);
c=data(101:130,1:4);
cc=data(131:150,1:4);
train_sample=cat(1,a,b,c);%组成训练样本(90*4)
test_sample=cat(1,aa,bb,cc);%组成测试样本(60*4)
k=5;
cha=zeros(1,90);
sum=0;
[i,j]=size(train_sample);
[u,v]=size(test_sample);
for x=1:u
for y=1:i
result=sqrt((test_sample(x,1)-train_sample(y,1)).^2+(test_sample(x,2)-train_sample(y,2)).^2+(test_sample(x,3)-train_sample(y,3)).^2+(test_sample(x,4)-train_sample(y,4)).^2);
cha(1,y)=result;
end;
[z,ind]=sort(cha);
m1=0;
m2=0;
m3=0;
for n=1:k
if ind(1,n)<+30
 
matlab
分类
测试
knn
训练
实现
样本
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