This package offers an implementation of CHAID, a type of decision tree technique for a nominal scaled dependent variable published in 1980 by Gordon V. Kass. CHAID stands for Chi-squared Automated Interaction Detection and detects interactions between categorized variables of a data set, one of which is the dependent variable. The remaining variables may or may not be ordered. An algorithm for recursive partitioning is implemented, based on maximizing the significance of a chi-squared statistic for cross-tabulations between the dependent variable and the predictors at each partition. The data are partitioned into mutually exclusive, exhaustive subsets that best describe the dependent variable. Multiway splits are used by default.
|Author||The FoRt Student Project Team 2009 and Torsten Hothorn|
|Date of publication||2015-08-03 19:21:40|
|Maintainer||Anjana K V <firstname.lastname@example.org>|