Evolving Multi-label Classification Rules with Gene Expression Programming: A Preliminary Study by:
José Ávila-Jiménez,
Eva Gibaja,
Sebastián Ventura
edited by: Emilio Corchado, Manuel Graña Romay, Alexandre Manhaes Savio| RIS | Export as RIS which can be imported into most citation managers |
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In Hybrid Artificial Intelligence Systems, Vol. 6077 (2010), pp. 9-16. doi:10.1007/978-3-642-13803-4_2 Key: citeulike:8938709
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AbstractThe 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.
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