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- Optimizing feature selection through binary charged system search
- Universidade Estadual Paulista (UNESP)
- Universidade de São Paulo (USP)
- Faculdade Sudoeste Paulista
- Feature selection aims to find the most important information from a given set of features. As this task can be seen as an optimization problem, the combinatorial growth of the possible solutions may be inviable for a exhaustive search. In this paper we propose a new nature-inspired feature selection technique based on the Charged System Search (CSS), which has never been applied to this context so far. The wrapper approach combines the power of exploration of CSS together with the speed of the Optimum-Path Forest classifier to find the set of features that maximizes the accuracy in a validating set. Experiments conducted in four public datasets have demonstrated the validity of the proposed approach can outperform some well-known swarm-based techniques. © 2013 Springer-Verlag.
- Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 8047 LNCS, n. PART 1, p. 377-384, 2013.
- Charged System Search
- Evolutionary Optimization
- Feature Felection
- Charged system searches
- Evolutionary optimizations
- Optimization problems
- Optimum-path forests
- Selection techniques
- Wrapper approach
- Image analysis
- Acesso restrito
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