A Self-Organizing Model for Logic Regression

Logic regression, as developed by Ruczinski, Kooperberg, and LeBlanc [1], is a multivariable regression methodology that constructs logical relationships among Boolean predictor variables that best predicts a Boolean dependent variable. More specifically, it finds a regression model of the form 01122[|]mmgEYbbLbLbL=+++ where both the coefficients 01,,...,mbbb and the logical expressions,1,...,jLjm= are determined, whereby a logical expression one means logical relationships among the predictor variables, such as 12",XX are true but not 5"X , or 357",,XXXare true but not 1X or 2"X In paper [1] the authors investigate the use a simulated annealing algorithm. In this paper. the Group Method of Data Handling (GMDH) is used.