Azzera filtri
Azzera filtri

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

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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.

Risposte (2)

Muhammad Kashif
Muhammad Kashif il 27 Set 2018
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.
  7 Commenti
Tanvir Kaisar
Tanvir Kaisar il 26 Feb 2019
Saba, I am facing the same problem. Did you find the solution to your problem? Can you please share it?
Mohsin Khan
Mohsin Khan il 24 Nov 2019
Modificato: Mohsin Khan il 24 Nov 2019
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);

Accedi per commentare.


yi du
yi du il 24 Lug 2022
but how to predict the new data?

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