Abstract
Cooperative Coevolution is a technique in the area of Evolutionary Computation. It has been applied to many combinatorial problems with great success. This contribution proposes a Cooperative Coevolution model for simultaneous performing some data reduction processes in classification with nearest neighbours methods through feature and instance selection.
In order to check its performance, we have compared the proposal with other evolutionary approaches for performing data reduction. Results have been analyzed and contrasted by using non-parametric statistical tests, finally showing that the proposed model outperforms the non-cooperative evolutionary techniques.
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Derrac, J., García, S., Herrera, F. (2009). A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds) Hybrid Artificial Intelligence Systems. HAIS 2009. Lecture Notes in Computer Science(), vol 5572. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02319-4_67
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DOI: https://doi.org/10.1007/978-3-642-02319-4_67
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