I am using the ksvm function from the library kernlab to generate an SVM classification. I am running the model with k-mean cross-validation, thus obtaining different accuracy. Is it possible to merge the different models obtained with the separate data set to generate a kind of median model, one that accounts for all the datasets used for the training?
Thank you
