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how to predict response using test data after using 'KFold ', 5 in case of SVM

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Saba Yousaf
Saba Yousaf 2018-9-27
回答： yi du 2022-7-24
Hi there...after training a model using following code Mdl = fitrsvm(predictortrain,response,'standardize', true, 'kFold', 5) now kindly tell me how can i calculate the response using 'Kfoldpredict' instead of predict and which parameter i have to pass for 'Kfoldpredict'. as i have seperate data for testing kindly let me know if you have any solution.

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Muhammad Kashif
Muhammad Kashif 2018-9-27
once you trained the model. now you want to use 'Kfoldpredict', first you validate your model. e.g;
Mdl = fitcecoc(features_train,labels_train,'Learners',t,'FitPosterior',1,...
'ClassNames',{'1','2','3','4','5','6','7'},...
'Verbose',2);
CVMdl = crossval(Mdl); % cross- validate Mdl
oosLoss = kfoldLoss(CVMdl);
label = predict(Mdl,features_test); % if want to predict
oofLabel = kfoldPredict(CVMdl);
i hope itwill help you.
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Tanvir Kaisar
Tanvir Kaisar 2019-2-26
Saba, I am facing the same problem. Did you find the solution to your problem? Can you please share it?
Mohsin Khan
Mohsin Khan 2019-11-24
编辑：Mohsin Khan 2019-11-24
You are not setting the right number of parameters;
Try this, will get right output with 5-fold
Mdl = fitrsvm(predictortrain,response,'standardize', true);
CVMdl = crossval(Mdl, 'kfold', 5);

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yi du
yi du 2022-7-24
but how to predict the new data?

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