Abstract
Grammatical Evolution (GE) is a grammar-based form of Genetic Programming. In GE, a Mapping Process (MP) and a Backus–Naur Form grammar (defined in the problem context) are used to transform each individual’s genotype into its phenotype form (functional representation). There are several MPs proposed in the state-of-the-art, each of them defines how the individual’s genes are used to build its phenotype form. This paper compares two MPs: the Depth-First standard map and the Position Independent Grammatical Evolution (πGE). The comparison was performed using as use case the problem of the selection and generation of features for pattern recognition problems. A Wilcoxon Rank-Sum test was used to compare and validate the results of the different approaches.
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Calzada-Ledesma, V., Puga-Soberanes, H.J., Rojas-Domínguez, A., Ornelas-Rodríguez, M., Carpio-Valadez, J.M., Gómez-Santillán, C.G. (2017). Comparing Grammatical Evolution’s Mapping Processes on Feature Generation for Pattern Recognition Problems. In: Melin, P., Castillo, O., Kacprzyk, J. (eds) Nature-Inspired Design of Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 667. Springer, Cham. https://doi.org/10.1007/978-3-319-47054-2_52
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DOI: https://doi.org/10.1007/978-3-319-47054-2_52
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