'''Chi-square automatic interaction detection''' ('''CHAID''') is a type of [[Decision tree learning|decision tree]] technique, based uponon adjusted significance testing ([[Bonferroni testing]]). The technique was developed in [[South Africa]] and was published in 1980 by Gordon V. Kass, who had completed a PhD thesis on this topic. CHAID can be used for prediction (in a similar fashion to [[regression analysis]], this version of CHAID being originally known as XAID) as well as classification, and for detection of interaction between variables. CHAID stands for '''CH'''i-squared '''A'''utomatic '''I'''nteraction '''D'''etection,is based uponon a formal extension of the US AID (Automatic Interaction Detection) and THAID (THeta Automatic Interaction Detection) procedures of the 1960s and 1970s, which in turn were extensions of earlier research, including that performed in the UK in the 1950s.
In practice, CHAID is often used in the context of [[direct marketing]] to select groups of consumers and predict how their responses to some variables affect other variables, although other early applications were in the field of medical and psychiatric research.
