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使用 Matlab 中的模糊工具箱，我尝试计算验证集上的误差。第一次交叉验证用于在训练和测试（验证）集中拆分初始训练数据。然而，在这个验证阶段，我也想为 genfis3 函数中的不同参数设置获取错误。我想将此函数中的第四个输入从 2 更改为 10 并计算平均误差。 

fismat3 = genfis3(X1,Y1,'sugeno',2);

整个代码：

 [m,~]=size(dataTrain);
    CVO = cvpartition(m,'k',10);
    err = zeros(CVO.NumTestSets,1);

    for i = 1:CVO.NumTestSets
     trIdx = CVO.training(i);
     teIdx = CVO.test(i);
     X1=Xtrain(trIdx,:);
     X2=Xtrain(teIdx,:);
     Y1=Ytrain(trIdx,:);
     Y2=Ytrain(teIdx,:);

     fismat3 = genfis3(X1,Y1,'sugeno',2);
     fismat3 = anfis([X1,Y1],fismat3);
     out1=evalfis(X2,fismat3);
     ee=Y2-out1;
     err(i)=mean(abs(ee));
end
Error32 = mean(err)
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1 回答 1

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弄清楚了：

[m,~]=size(dataTrain);
CVO = cvpartition(m,'k',10);
err = zeros(CVO.NumTestSets,9);%9 denotes the amount of different parameter setting you want to validate
out = zeros(CVO.NumTestSets,1);
ee = zeros(CVO.NumTestSets,1);
for i = 1:CVO.NumTestSets %voor iedere test en training set
     trIdx = CVO.training(i); %selecteer index training data
     teIdx = CVO.test(i); %selecteer index test data
     X1=Xtrain(trIdx,:); %Creer training input variabelen
     X2=Xtrain(teIdx,:); %Creer test input variabelen
     Y1=Ytrain(trIdx,:); % Creer training output variable
     Y2=Ytrain(teIdx,:); % Creer test output variable

for j = 2:10     
     fismat3 = genfis3(X1,Y1,'sugeno',j); %creer voor iedere test en training set een andere genfis 3
     fismat3 = anfis([X1,Y1],fismat3); %optimaliseer using anfis
     out1=evalfis(X2,fismat3);          
     ee=Y2-out1;
     err(i,j-1)=mean(abs(ee));
end

end

Error = mean(err)
于 2016-01-24T19:17:11.820 回答