说明：  ：将信息论中熵的概念应用到特征选择中，定义了两种信息测度评价特征——误差熵和混叠熵，然后阐述了两种定义的不 用物理意义，分析了计算熵中最关键的区间划分问题，并提出一种较好的区间划分方法。
(: The concept of entropy in information theory applied to feature selection, the definition of information measure evaluation of two features- error entropy and mixing entropy, and then describes the two definitions do not have the physical meaning of the calculation of entropy in the range of the most critical partitioning problem and propose a better method of interval division.)