A Survey on Evolutionary Instance Selection and Generation

Joaquín Derrac, Salvador García and Francisco Herrera
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Joaquín Derrac: University of Granada, Spain
Salvador García: University of Jaén, Spain
Francisco Herrera: University of Granada, Spain

International Journal of Applied Metaheuristic Computing (IJAMC), 2010, vol. 1, issue 1, 60-92

Abstract: The use of Evolutionary Algorithms to perform data reduction tasks has become an effective approach to improve the performance of data mining algorithms. Many proposals in the literature have shown that Evolutionary Algorithms obtain excellent results in their application as Instance Selection and Instance Generation procedures. The purpose of this paper is to present a survey on the application of Evolutionary Algorithms to Instance Selection and Generation process. It will cover approaches applied to the enhancement of the nearest neighbor rule, as well as other approaches focused on the improvement of the models extracted by some well-known data mining algorithms. Furthermore, some proposals developed to tackle two emerging problems in data mining, Scaling Up and Imbalance Data Sets, also are reviewed.

Date: 2010
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