Machine Learning with R Cookbook - Second Edition

How it works...

In this recipe, we used a conditional inference tree to build a classification tree. The use of ctree is similar to rpart. Therefore, you can easily test the classification power using either a traditional decision tree or a conditional inference tree while confronting classification problems. Next, we obtain the node details of the classification tree by examining the built model. Within the model, we discover that ctree provides information similar to a split condition, criterion (1 - p-value), statistics (test statistics), and weight (the case weight corresponding to the node). However, it does not offer as much information as rpart does through the use of the summary function.