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A Survey on Evolutionary Instance Selection and Generation

A Survey on Evolutionary Instance Selection and Generation

Joaquín Derrac, Salvador García, Francisco Herrera
Copyright: © 2010 |Volume: 1 |Issue: 1 |Pages: 33
ISSN: 1947-8283|EISSN: 1947-8291|ISSN: 1947-8283|EISBN13: 9781616929664|EISSN: 1947-8291|DOI: 10.4018/jamc.2010102604
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MLA

Derrac, Joaquín, et al. "A Survey on Evolutionary Instance Selection and Generation." IJAMC vol.1, no.1 2010: pp.60-92. http://doi.org/10.4018/jamc.2010102604

APA

Derrac, J., García, S., & Herrera, F. (2010). A Survey on Evolutionary Instance Selection and Generation. International Journal of Applied Metaheuristic Computing (IJAMC), 1(1), 60-92. http://doi.org/10.4018/jamc.2010102604

Chicago

Derrac, Joaquín, Salvador García, and Francisco Herrera. "A Survey on Evolutionary Instance Selection and Generation," International Journal of Applied Metaheuristic Computing (IJAMC) 1, no.1: 60-92. http://doi.org/10.4018/jamc.2010102604

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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.

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