Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to retrieve the minimum estimation error using cross-validation:

1. Apply tune.svm on the training dataset, trainset, with the 10-fold cross-validation as the tuning control (if you find an error message, such as could not find function predict.func, please clear the workspace, restart the R session, and reload the e1071 library again):

        > tuned = tune.svm(churn~., data = trainset, gamma = 10^-2, cost         = 10^2, tunecontrol=tune.control(cross=10))

2. Next, you can obtain the summary information of the model, tuned:

        > summary(tuned)
    
        Output
        Error estimation of 'svm' using 10-fold cross validation:        0.08164651

3. Then, you can access the performance details of the tuned model:

 > tuned$performances Output ...