Among the existing feature selection/synthesis approaches, Coevolutionary Feature Synthesis (CFS) based on Coevolutionary Genetic Programming (CGP) has shown good performance on a variety of applications. In this paper, we propose an MDL-based fitness function to help pick a reasonable number of synthesized features which is equal to the number of subpopulations. It naturally balances the feature transformation complexity and classification performance. Experiments on a real image database show that the new fitness function solves the problem quite well.
@INPROCEEDINGS { LiBhanuKrawiec07geccoPoster,
ABSTRACT = { Among the existing feature selection/synthesis approaches, Coevolutionary Feature Synthesis (CFS) based on Coevolutionary Genetic Programming (CGP) has shown good performance on a variety of applications. In this paper, we propose an MDL-based fitness function to help pick a reasonable number of synthesized features which is equal to the number of subpopulations. It naturally balances the feature transformation complexity and classification performance. Experiments on a real image database show that the new fitness function solves the problem quite well. },
AUTHOR = { Rui Li and Bir Bhanu and Krzysztof Krawiec },
BOOKTITLE = { Genetic and Evolutionary Computation Conference GECCO },
EDITOR = { Dirk Thierens },
ISBN = { 978-1-59593-698-1 },
PAGES = { 489--489 },
PUBLISHER = { Association for Computing Machinery },
TITLE = { On the Number of Subpopulations in Coevolutionary Computation: A Database Application },
YEAR = { 2007 },
}