Center for Secure Cyberspace, Computer Science,Louisiana Tech University, Nethken Hall, 600 W. Arizona Ave., Ruston,LA 71272, USA.
IEEE Trans Pattern Anal Mach Intell. 2010 Jul;32(7):1342-3. doi: 10.1109/TPAMI.2010.62.
We derive the feature selection criterion presented in [CHECK END OF SENTENCE] and [CHECK END OF SENTENCE] from the multidimensional mutual information between features and the class. Our derivation: 1) specifies and validates the lower-order dependency assumptions of the criterion and 2) mathematically justifies the utility of the criterion by relating it to Bayes classification error.
我们从特征与类之间的多维互信息中推导出了[CHECK END OF SENTENCE]和[CHECK END OF SENTENCE]中提出的特征选择准则。我们的推导：1）指定并验证了准则的低阶依赖假设，2）通过将其与贝叶斯分类错误相关联，从数学上证明了准则的效用。
