关键词: 特征选择, 互信息, Renyi熵, 熵估计

Abstract: Normalized mutual information feature selection method was proposed based on quadratic Renyi's entropy. This method could efficiently estimate the mutual information, so that the computational complexity was greatly reduced. At the same time, the normalized mutual information feature selection method and embedding method were combined to get a two-stage feature selection algorithm, which could find more characteristic feature subsets. The experimental results compared with the other similar algorithms show that the proposed method can effectively reduce the computational complexity.

Key words: feature selection, mutual information, Renyi entropy, entropy estimation