Year: 2022
Type: preprint
Abstract: Multi Expression Programming (MEP) is a Genetic Programming variant that encodes multiple solutions in a single chromosome. This paper introduces and deeply describes several strategies for solving binary and multi-class classification problems within the multi solutions per chromosome paradigm of MEP. Extensive experiments on various classification problems are performed. MEP shows similar or better performances than other methods used for comparison (namely Artificial Neural Networks and Linear Genetic Programming).
Source: Research Square
Author: Mihai Oltean
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W4220932420