Yang Sheng, Gu Jun
Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai 200030, China.
J Zhejiang Univ Sci. 2004 Nov;5(11):1382-91. doi: 10.1631/jzus.2004.1382.
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.
互信息是用于特征子集的一种重要信息度量。本文提出了一种哈希机制来计算特征子集上的互信息。冗余 - 协同系数是通过互信息定义的一种用于表达类别特征的新颖的特征冗余和协同度量。应用信息最大化规则推导了基于互信息和冗余 - 协同系数的启发式特征子集选择方法。我们的实验结果表明了这种新特征选择方法的良好性能。
