cart_iris.txt

matlab数据挖掘算法。实用cart决策树进行分类

function CART_iris()
DT_mean=1-DecisionT(datainput,datatarget,testinput,testtarget,error_value,trainnum);  %决策树错误率
%for Classification Tree
%训练决策树
function DT_mean=DecisionT(datainput,datatarget,testinput,testtarget,error_value,trainnum)
fprintf(1,'Classification tree...\n');
datatarget= entree_transformtarget(datatarget');%数值型类标转化为字符型类标
t = treefit(datainput,datatarget);
%t = treeprune(t,'level',2);
% treedisp(t,'names',{'SL' 'SW' 'PL' 'PW'}); 

sfit = treeval(t,testinput);   % Find assigned class numbers
sfit=t.classname(sfit);
testtarget=entree_transformtarget(testtarget');%数值型类标转化为字符型类标
%mean(sfit==datatarget)         % Compute proportion correctly-用于回归
DT_mean=mean(strcmp(sfit,testtarget'));  % Compute proportion correctly 分类正确率
 %保存一个好一些决策树
 DT_error=1-DT_mean;
 if DT_error<error_value
  filename=strcat('CART_iris_',dec2base(trainnum,10));
  save(filename, 't');
 else
 end
 %----------------------目标数据转换为字符型－数据转换-----------------------------
function datatarget=entree_transformtarget(datatarget)
datatarget=datatarget';
[rows cols]=size(datatarget);
for i=1:rows
    [xx classlabel]=max(datatarget(i,:));
    classlabel=dec2base(classlabel,10);
    tmpdatatarget(i)={classlabel};
end
datatarget=tmpdatatarget;