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Use of Multiobjective Genetic Algorithms in Feature Selection

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3 Author(s)
Spolaor, N. ; Univ. Fed. do ABC Santo Andre, Santo Andre, Brazil ; Lorena, A.C. ; Lee, H.D.

The intelligent analysis of Databases may be affected by the presence of unimportant features, which motivates the application of Feature Selection. By treating this task as a search and optimization process, it is possible to use the synergy between Genetic Algorithms and Multi-objective Optimization to carry out the search for (quasi) optimal subsets of features considering possible conflicting importance criteria. This work presents an application of Multi-objective Genetic Algorithms to the Feature Selection problem, combining different criteria measuring the importance of the subsets of features.

Published in:

Neural Networks (SBRN), 2010 Eleventh Brazilian Symposium on

Date of Conference:

23-28 Oct. 2010