How to predict responses of new data from a crossvalidated SVR model

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NCA 2023-2-2
回答： Dr. JANAK TRIVEDI 2023-2-2
Hi there
I have trained and cross validated my Support Vector Machine regressor model (CValidated_Mdl) with KFold cross validation technique.
I know I can predict responses by using YFit= kfoldPredict(CValidated_Mdl) where YFit are the new responses predicted by the model.
I also have a new set of data(unseen by model) which I will like to use to test the performance of my CValidated_Mdl.
This new and unseen data is called X_test.
I am not sure of how to use the cross validated model (CValidated_Mdl) to predict responses from the X_test data
I have tried YFit= kfoldPredict(CValidated_Mdl, X_test) without success
Can you advise please
Thank You

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采纳的回答

Dr. JANAK TRIVEDI
You can use the predict function in MATLAB to predict responses using the cross-validated model (CValidated_Mdl) and the new data X_test. The code would look like this:
YFit = predict(CValidated_Mdl.Trained{1}, X_test);
Note that CValidated_Mdl.Trained{1} is the trained SVM model for the first fold in the cross-validation, you can use any fold that you think has the best performance.

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