title: Feature selection based on mutual information and redundancy-synergy coefficient.
abstract: Mutual information is an important information measure for feature subset. In this paper, a hashing mechanism is proposed to calculate the mutual information on the feature subset. Redundancy-synergy coefficient, a novel redundancy and synergy measure of features to express the class feature, is defined by mutual information. The information maximization rule was applied to derive the heuristic feature subset selection method based on mutual information and redundancy-synergy coefficient. Our experiment results showed the good performance of the new feature selection method.
authors.affiliation: Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030, China. yangsheng@sjtu.edu.cn.
authors.forename: Sheng
authors.initials: S
authors.lastname: Yang
authors.forename: Jun
authors.initials: J
authors.lastname: Gu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003628:Database Management Systems; D016208:Databases, Factual; D040362:Geographic Information Systems; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011381:Programming Languages; D012984:Software; D014584:User-Computer Interface