Enhancement of MahalanobisTaguchi System via Rough Sets based Feature Selection
Paper develops a new feature selection method for MahalanobisTaguchi System. New feature selection includes regularization or penalty for over-fitting. It also describes causal relationship between variables and classes. Results of proposed method are compared with those of other classification methods.
rough sets feature selection regularization data mining mahalanobis taguchi system orthogonal arrays over-fitting conditional probability ifthen rules