Measuring performance differences between models with the caret package

In the previous recipe, we introduced how to generate ROC curves for each generated model, and have the curve plotted on the same figure. Apart from using an ROC curve, one can use the resampling method to generate statistics of each fitted model in ROC, sensitivity, and specificity metrics. Therefore, we can use these statistics to compare the performance differences between each model. In the following recipe, we will introduce how to measure performance differences between fitted models with the caret package.

Getting ready

One needs to have completed the previous recipe by storing the glm fitted model, svm fitted model, and the rpart fitted model into...