Title: Multi-objective classification based on NSGA-II

Authors: Binping Zhao; Yu Xue; Bin Xu; Tinghuai Ma; Jingfa Liu

Addresses: School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Engineering Research Center of Communication and Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China; Jiangsu Engineering Research Center of Communication and Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210044, China ' School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing, 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China ' School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

Abstract: The fast and elitist non-dominated sorting genetic algorithm-II (NSGA-II) is currently the most popular multi-objective evolutionary algorithm (MOEA). NSGA-II has been shown to work well for two-objective problems by attaining near-optimal diverse and uniformly distributed Pareto solutions. To use the powerful multi-objective optimisation performance of NSGA-II directly and conveniently, an optimisation classification model is presented. In the optimisation classification model, a linear equation set is constructed according to classification problems. In this paper, we introduced NSGA-II to solve the optimisation classification model. Besides, eight different datasets have been chosen in experiments to test the performance of NSGA-II. The results show that NSGA-II is able to find much better spread of solutions and has high classification accuracy and robustness.

Keywords: evolutionary classification algorithm; non-dominated sorting genetic algorithm-II; NSGA-II; multi-objective; optimisation.

DOI: 10.1504/IJCSM.2018.10017540

International Journal of Computing Science and Mathematics, 2018 Vol.9 No.6, pp.539 - 546

Received: 25 Jan 2018
Accepted: 23 Apr 2018

Published online: 16 Nov 2018 *

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