We find that GA feature selection always significantly outperforms the MBLP variant without selection and that feature ordering and weighting with CA significantly outperforms a situation where no weighting is used.
gA selection does not significantly do better than simple iterative feature selection methods, and gA weighting and ordering reach only similar performance as current information-theoretic feature weighting methods.