Title: A new memetic approach for the classification rules extraction problem

Authors: Sadjia Benkhider; Habiba Drias

Addresses: Department of Computer Sciences, Laboratory of Artificial Intelligence Research LRIA, University of Sciences and Technology, P.O. Box 32, El Alia, 16111 Algiers, Algeria ' Department of Computer Sciences, Laboratory of Artificial Intelligence Research LRIA, University of Sciences and Technology, P.O. Box 32, El Alia, 16111 Algiers, Algeria

Abstract: This paper presents a memetic algorithm applied to the classification rules extraction problem. In our new approach, our aim is to obtain a better results accuracy relatively to that obtained by a standard genetic algorithm (GA). A memetic algorithm is based on a GA which is improved by hybridising a local search approach. We made a hybrid method to compute a model of classification. In the literature, there are many hybridisation forms: in this paper, we have chosen to make our local search algorithm also based on a genetic approach so our hybridisation is purely evolutionary.

Keywords: data mining; evolutionary computation; classification rules extraction; Michigan approach; memetics; meta-meta hybridisation; genetic algorithms; memetic algorithms; local search.

DOI: 10.1504/IJDMMM.2013.057682

International Journal of Data Mining, Modelling and Management, 2013 Vol.5 No.4, pp.318 - 332

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 18 Nov 2013 *

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