Social and Behavioral Sciences Commons^™

A Tandem Evolutionary Algorithm For Identifying Causal Rules From Complex Data, John P. Hanley, Donna M. Rizzo, Jeffrey S. Buzas, Margaret J. Eppstein

College of Engineering and Mathematical Sciences Faculty Publications

We propose a new evolutionary approach for discovering causal rules in complex classification problems from batch data. Key aspects include (a) the use of a hypergeometric probability mass function as a principled statistic for assessing fitness that quantifies the probability that the observed association between a given clause and target class is due to chance, taking into account the size of the dataset, the amount of missing data, and the distribution of outcome categories, (b) tandem age-layered evolutionary algorithms for evolving parsimonious archives of conjunctive clauses, and disjunctions of these conjunctions, each of which have probabilistically significant associations with outcome …