A niching algorithm to learn discriminant functions with multi-label patterns

Authors:
J. L. Ávila;E. L. Gibaja;A. Zafra;S. Ventura
Affiliations:
Department of Computer Science and Numerical Analysis, University of Córdoba;Department of Computer Science and Numerical Analysis, University of Córdoba;Department of Computer Science and Numerical Analysis, University of Córdoba;Department of Computer Science and Numerical Analysis, University of Córdoba
Venue:
IDEAL'09 Proceedings of the 10th international conference on Intelligent data engineering and automated learning
Year:
2009

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Abstract

In this paper we present a Gene Expression Programming algorithm for multi-label classification. This algorithm encodes each individual into a discriminant function that shows whether a pattern belongs to a given class or not. The algorithm also applies a niching technique to guarantee that the population includes functions for each existing class. Our proposal has been compared with some recently published algorithms. The results on several datasets demonstrate the feasibility of this approach to tackle with multi-label problems.