Evolving multi-label classification rules with gene expression programming: a preliminary study

Authors:
José Luis Ávila-Jiménez;Eva Gibaja;Sebastián Ventura
Affiliations:
Department of Computer Sciences and Numerical Analysis, University of Córdoba;Department of Computer Sciences and Numerical Analysis, University of Córdoba;Department of Computer Sciences and Numerical Analysis, University of Córdoba
Venue:
HAIS'10 Proceedings of the 5th international conference on Hybrid Artificial Intelligence Systems - Volume Part II
Year:
2010

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Abstract

The present work expounds a preliminary work of a genetic programming algorithm to deal with multi-label classification problems The algorithm uses Gene Expression Programming and codifies a classification rule into each individual A niching technique assures diversity in the population The final classifier is made up by a set of rules for each label that determines if a pattern belongs or not to the label The proposal have been tested over several domains and compared with other multi-label algorithms and the results shows that it is specially suitable to handle with nominal data sets.