Machine Learning with R Cookbook - Second Edition

How to do it...

Perform the following steps to validate the prediction performance of a classification tree:

1. You can use the predict function to generate a predicted label of testing the dataset:

        > predictions = predict(churn.rp, testset, type="class")

2. Use the table function to generate a classification table for the testing dataset:

        > table(testset$churn, predictions)
        Output
                predictions
                  yes  no
              yes 100  41
              no   18 859  

3. One can further generate a confusion matrix using the confusionMatrix function provided in the caret package:

        > library(caret)        > confusionMatrix(table(predictions, testset$churn))        Output        Confusion Matrix and Statistics        predictions yes no                yes 100 18                no 41 859                   Accuracy : 0.942                      95% CI : (0.9259, 0.9556) No Information Rate ...