Machine Learning with R Cookbook - Second Edition

How it works...

In this recipe, we demonstrated how to measure the performance differences among three fitted models using the resampling method. First, we use the resample function to generate the statistics for each fitted model (svm.model, glm.model, and rpart.model). Then, we can use the summary function to obtain the statistics of these three models in the ROC, sensitivity, and specificity metrics. Next, we can apply a dotplot on the resampling result to see how ROC varied between each model. Last, we use a box-whisker plot on the resampling results to show the box-whisker plot for different models in the ROC, sensitivity, and specificity metrics on a single plot.