A grammar-guided genetic programming algorithm for multi-label classification

Authors:
Alberto Cano;Amelia Zafra;Eva L. Gibaja;Sebastián Ventura
Affiliations:
Department of Computer Science and Numerical Analysis, University of Cordoba, Cordoba, Spain;Department of Computer Science and Numerical Analysis, University of Cordoba, Cordoba, Spain;Department of Computer Science and Numerical Analysis, University of Cordoba, Cordoba, Spain;Department of Computer Science and Numerical Analysis, University of Cordoba, Cordoba, Spain
Venue:
EuroGP'13 Proceedings of the 16th European conference on Genetic Programming
Year:
2013

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Abstract

Multi-label classification is a challenging problem which demands new knowledge discovery methods. This paper presents a Grammar-Guided Genetic Programming algorithm for solving multi-label classification problems using IF-THEN classification rules. This algorithm, called G3P-ML, is evaluated and compared to other multi-label classification techniques in different application domains. Computational experiments show that G3P-ML often obtains better results than other algorithms while achieving a lower number of rules than the other methods.