Machine Learning with R Cookbook - Second Edition

Measuring the prediction performance of a recursive partitioning tree

Since we built a classification tree in the previous recipes, we can use it to predict the category (class label) of new observations. Before making a prediction, we first validate the prediction power of the classification tree, which can be done by generating a classification table on the testing dataset. In this recipe, we will introduce how to generate a predicted label versus a real label table with the predict function and the table function, and explain how to generate a confusion matrix to measure the performance.