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European Conference on Genetic Programming

EuroGP 2013: Genetic Programming pp 217–228Cite as

A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7831))

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.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Numerical Analysis, University of Cordoba, 14071, Cordoba, Spain

    Alberto Cano, Amelia Zafra, Eva L. Gibaja & Sebastián Ventura

Authors
  1. Alberto Cano
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  2. Amelia Zafra
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  3. Eva L. Gibaja
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  4. Sebastián Ventura
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Editor information

Editors and Affiliations

  1. Institute of Computing Science, Poznan University of Technology, Piotowo 2, 60-965, Poznań, Poland

    Krzysztof Krawiec

  2. School of Computer Science, The University of Birmingham, B15 2TT, Edgbaston, Birmingham, UK

    Alberto Moraglio

  3. Geisel School of Medicine, Dartmouth College, 03755, Hanover, NH, USA

    Ting Hu

  4. Department of Computer Engineering, Istanbul Technical University, 34469, Masla, Istanbul, Turkey

    A. Şima Etaner-Uyar

  5. Institute of Computer Graphics and Algorithms, Vienna University of Technology, 1040, Vienna, Austria

    Bin Hu

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Cano, A., Zafra, A., Gibaja, E.L., Ventura, S. (2013). A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification. In: Krawiec, K., Moraglio, A., Hu, T., Etaner-Uyar, A.Ş., Hu, B. (eds) Genetic Programming. EuroGP 2013. Lecture Notes in Computer Science, vol 7831. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37207-0_19

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  • DOI: https://doi.org/10.1007/978-3-642-37207-0_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37206-3

  • Online ISBN: 978-3-642-37207-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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