Genetic Programming Symbolic Classification: A Study (original) (raw)
While Symbolic Regression (SR) is a well-known offshoot of Genetic Programming, Symbolic Classification (SC), by comparison, has received only meager attention. Clearly, regression is only half of the solution. Classification also plays an important role in any well rounded predictive analysis tool kit. In several recent papers, SR algorithms are developed which move SR into the ranks of extreme accuracy. In an additional set of papers algorithms are developed designed to push SC to the level of basic classification accuracy competitive with existing commercially available classification tools. This paper is a simple study of four proposed SC algorithms and five well-known commercially available classification algorithms to determine just where SC now ranks in competitive comparison. The four SC algorithms are: simple genetic programming using argmax referred to herein as (AMAXSC); the M2GP algorithm; the MDC algorithm, and Linear Discriminant Analysis (LDA). The five commercially a...