CHAID stands for Chi-squared Automatic Interaction Detector. It is a method for building classification trees and regression trees from a learning sample comprising already-classified objects. An essential feature is the use of the chi-square test for contingency tables to decide which variables are of maximal importance for classification. Another aspect of CHAID is its ability to build non-binary classification trees - i.e. trees where more than two branches may go from a node.

CHAID can deal with multi-way contingency tables, when both predictors and response categorical variables have many classes. For this reason CHAID is widely used, for example, for market segmentation studies.