Machine Learning with R Cookbook - Second Edition

How it works...

To visualize the node detail of the conditional inference tree, we can apply the plot function on a built classification model. The output figure reveals that every intermediate node shows the dependent variable name and the p-value. The split condition is displayed on the left and right branches. The terminal nodes show the number of categorized observations, n, and the probability of a class label of either 0 or 1.

Taking the preceding as an example, we first build a classification model using total_day_charge as the only feature and churn as the class label. The built classification tree shows that when total_day_charge is above 48.18, the lighter gray area is greater than the darker gray in node 9, which indicates that ...