A new memetic approach for the classification rules extraction problem

Sadjia Benkhider and Habiba Drias

International Journal of Data Mining, Modelling and Management, 2013, vol. 5, issue 4, 318-332

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. (search for similar items in EconPapers)
Date: 2013
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