BEAGLE—A DARWINIAN APPROACH TO PATTERN RECOGNITION

Abstract

BEAGLE (Biological Evolutionary Algorithm Generating Logical Expressions) is a computer package for producing decision‐rules by induction from a database. It works on the principle of “Naturalistic Selection” whereby rules that fit the data badly are “killed off” and replaced by “mutations” of better rules or by new rules created by “mating” two better adapted rules. The rules are Boolean expressions represented by tree structures. The software consists of two Pascal programs, HERB (Heuristic Evolutionary Rule Breeder) and LEAF (Logical Evaluator And Forecaster). HERB improves a given starting set of rules by running over several simulated generations. LEAF uses the rules to classify samples from a database where the correct membership may not be known. Preliminary tests on three different databases have been carried out—on hospital admissions (classing heart patients as deaths or survivors), on athletic physique (classing Olympic finalists as long‐distance runners or sprinters) and on football results (categorizing games into draws and non‐draws). It appears from the tests that the method works better than the standard discriminant analysis technique based on a linear discriminant function, and hence that this long‐neglected approach warrants further investigation.