Classification and Regression Trees

Classification and regression tree models (CARTs) are computationally intensive methods that are used in situations where there are many explanatory variables and user would like guidance about, possibly, including them in the model: classification trees are where the outcome is discrete and regression trees where the outcome is continuous. A CART model is fitted using binary recursive partitioning, whereby the data are successively split along co-ordinate axes of each of the explanatory variables so that, at any node, the split which maximally distinguishes the response variable in the left and the right branches is selected. Classification trees, for discrete outcomes, are derived using the same R functions…