A Review of Multi-Label Classification Methods - LPIS

In the future we intend to perform a finer-grained categorization of the different multi-labelclassification methods and perform more extensive experiments with more data sets and methods. Wealso intend to perform a comparative experimental study of problem adaptation methods.REFERENCESAha, D.W., Kibler, D., & Albert, M.K. (1991), 'Instance-based learning algorithms', MachineLearning, vol. 6, no. 1, pp. 37-66 .Boutell, M.R., Luo, J., Shen, X. & Brown, C.M. (2004), 'Learning multi-label scene classification',Pattern Recognition, vol. 37, no. 9, pp. 1757-71.Chang, C.-C., & Lin, C.-J. (2004), 'LIBSVM : a library for support vector machines', Softwareavailable at http://www.csie.ntu.edu.tw/~cjlin/libsvmClare, A. & King, R.D. (2001), 'Knowledge Discovery in Multi-Label Phenotype Data', paperpresented to Proceedings of the 5th European Conference on Principles of Data Mining andKnowledge Discovery (PKDD 2001), Freiburg, Germany.Diplaris, S., Tsoumakas, G., Mitkas, P. & Vlahavas, I. (2005), 'Protein Classification with MultipleAlgorithms', paper presented to Proceedings of the 10th Panhellenic Conference on Informatics(PCI 2005), Volos, Greece, November.Elisseeff, A. & Weston, J. (2002), 'A kernel method for multi-labelled classification', paper presentedto Advances in Neural Information Processing Systems 14.Freund, Y. & Schapire, R.E. (1997), 'A decision-theoretic generalization of on-line learning and anapplication to boosting', Journal of Computer and System Sciences, vol. 55, no. 1, pp. 119-39.Godbole, S. & Sarawagi, S. (2004), 'Discriminative Methods for Multi-labeled Classification', paperpresented to Proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and DataMining (PAKDD 2004).Goncalves, T. & Quaresma, P. (2003), 'A Preliminary Approach to the Multilabel ClassificationProblem of Portuguese Juridical Documents', paper presented to Proceedings of the 11thPortuguese Conference on Artificial Intelligence (EPIA '03).