交叉验证算法源码程序 - matlab算法设计

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标题：交叉验证算法源码程序
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所属分类: 算法设计资源类型：文件大小: 230.57 KB 上传时间: 2016-01-27 18:18:06 下载次数: 8 资源积分：1分提供者: 马云交叉验证算法源码程序

内容：
交叉验证算法源码程序，程序员在编程的过程中可以参考学习使用，希望对IT程序员有用，此源码程序简单易懂、方便阅读，有很好的学习价值！

function [acc_mean,acc_std]=crossvalidate(sonar,fold,signal)

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

%sonar is the all data include the class

%fold is the number of crossvalidate

%signal is the signal of classification, if n=0 is decision tree

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

[row column]=size(sonar);

label=sonar(:,column);

classnum=max(label);

start1=1;

for i=1:classnum

[a,b]=find(label==i);

datai=sonar(a,:); %select the i class data

[rr1,cc1]=size(datai);

start1=1;

%%%%%%%%%part the i class in (fold)%%%%%%%%%%%%%%%%%%%%%

for j=1:fold-1

a1=round(length(a)/fold);

a2=a1-1;

%fun1=strcat('x*',num2str(a1),'+y*',num2str(a2),'=',num2str(rr1));

%fun2=strcat('x+y=',num2str(fold));

%[x,y]=solve(fun1,fun2)

%[x,y] = solve('x*a1+a2*y=rr1','x+y=fold')

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

A=[a1 a2;1 1];

b=[rr1 fold]';

x=A\b;

if (j<x(1)+1)

everynum=a1;

else

everynum=a2;

end

start2=start1+everynum-1;

eval(['data' num2str(i) num2str(j) '=datai([start1:start2],:);']);

start1=start2+1;

end

eval(['data' num2str(i) num2str(fold) '=datai([start1:length(a)],:);']);

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

for j=1:fold

eval(['part' num2str(j) '=[];']);

for i=1:classnum

eval(['part' num2str(j) '=[part' num2str(j) ';data' num2str(i) num2str(j) '];']);

end

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

accu_m=[];

Samples=[];

Labels=[];

column-1;

for j=1:fold

Samples=[];

Labels=[];

testS=[];

testL=[];

for i=1:fold

if (i~=j)

eval(['Samples=[Samples;part' num2str(i) '(:,1:column-1)];'])

eval(['Labels=[Labels;part' num2str(i) '(:,column)];'])

end

eval(['testS=part' num2str(j) '(:,1:column-1);'])

eval(['testL=part' num2str(j) '(:,column);'])

if (signal==0)

t = treefit(Samples,Labels,'method','classification'); % create decision tree

sfit = treeval(t,testS); % find assigned class numbers

ClassRate=length(find((sfit-testL)==0))/length(testL);

end

accu_m(j)=ClassRate;

end

acc_mean=mean(accu_m);

acc_std=std(accu_m);

accu_m

文件列表（点击上边下载按钮，如果是垃圾文件请在下面评价差评或者投诉）:

交叉验证算法源码程序/
交叉验证算法源码程序/code/
交叉验证算法源码程序/code/NDT.mat
交叉验证算法源码程序/code/Untitled8.m
交叉验证算法源码程序/code/crossvalidate.m

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