Newton Spolaôr,  Ana Carolina Lorena,  Huei Diana Lee. 

The occurrence of irrelevant and/or redundant features in Databases can degrade the performance of computational processes for knowledge extrac- tion, motivating the application of a Feature Selection process. Multi-objective Genetic Algorithms can help identifying subsets of features which optimize com- binations of possibly conflicting feature importance measures. This paper pre- sents the use of Multi-objective Genetic Algorithms in Feature Selection, inves- tigating the use of different combinations of feature importance criteria in both labeled and unlabeled datasets.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2011/0060.pdf

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