Performing cross-validation with the caret package
The caret (classification and regression training) package contains many functions in regard to the training process for regression and classification problems. Similar to the e1071 package, it also contains a function to perform the k-fold cross validation. In this recipe, we will demonstrate how to perform the k-fold cross validation using the caret package.
Getting ready
In this recipe, we will continue to use the telecom churn dataset as the input data source to perform the k-fold cross validation.
How to do it...
Perform the following steps to perform the k-fold cross-validation with the caret package:
- First, set up the
controlparameter to train the 10-fold cross validation in3repetitions:
> control = trainControl(method="repeatedcv", number=10,
repeats=3) - Then, you can train the classification model using the telecom
churndata withrpart:
> model = train(churn~., data=trainset, method="rpart",
preProcess...
