Feature Selection for Multi-label Classification Problems

Doquire, Gauthier;Verleysen, Michel
(2011) 11th international work-conference on artificial neural networks (IWANN 2011) — Location: Torremolinos (Spain) (8.June.2011)

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This paper proposes the use of mutual information for feature selection in multi-label classification, a surprisingly almost not studied problem. A pruned problem transformation method is first applied, transforming the multi-label problem into a single-label one. A greedy feature selection procedure based on multidimensional mutual information is then conducted. Results on three databases clearly demonstrate the interest of the approach which allows one to sharply reduce the dimension of the problem and to enhance the performance of classifiers.
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Doquire, G., & Verleysen, M. (2011). Feature Selection for Multi-label Classification Problems. In Joan Cabestany (ed.), Advances in Computational Intelligence (p. p. 9-16). Springer. https://doi.org/10.1007/978-3-642-21501-8_2