Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining

Book Chapter 2005

Authors: José Ramón Cano De Amo, Francisco Herrera Triguero, Manuel Lozano

Pages 21-39

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Cano De Amo, J. R., Herrera Triguero, F., & Lozano, M. (2005). Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining (A. Ghosh & L. C. Jain, Eds.). Berlin, Heidelberg: Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-32358-9_2

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Abstract

Evolutionary algorithms are adaptive methods based on natural evolution that may be used for search and optimization. As instance selection can be viewed as a search problem, it could be solved using evolutionary algorithms.

Details

Editors: Ashish Ghosh, Lakhmi Jain
DOI: 10.1007/3-540-32358-9_2
Publisher: Springer Berlin Heidelberg
City: Berlin, Heidelberg
ISBN Number: 978-3-540-32358-7