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

  • Alberto Cano
  • Amelia Zafra
  • Eva L. Gibaja
  • Sebastián Ventura
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Multi-label classification grammar-guided genetic programming rule learning 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Alberto Cano
    • 1
  • Amelia Zafra
    • 1
  • Eva L. Gibaja
    • 1
  • Sebastián Ventura
    • 1
  1. 1.Department of Computer Science and Numerical AnalysisUniversity of CordobaCordobaSpain

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