Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to retrieve the minimum estimation errors by performing cross-validation with the bagging method:

1. First, we use bagging.cv to make a 10-fold classification on the training dataset with 10 iterations:

        > churn.baggingcv = bagging.cv(churn ~ ., v=10, data=trainset,        mfinal=10)  

2. You can then obtain the confusion matrix from the cross-validation results:

        > churn.baggingcv$confusion
        Output
                       Observed Class
        Predicted Class  yes   no
                    no   100 1938
                    yes  242   35  

3. Lastly, you can retrieve the minimum estimation errors from the cross-validation results:

        > churn.baggingcv$error
        Output
        [1] 0.05831533