On the Feature Selection Criterion Based on an Approximation of Multidimensional Mutual Information

被引：45
|
作者：
Balagani, Kiran S. [1 ]
Phoha, Vir V. [1 ]
机构：
[1] Louisiana Tech Univ, Ctr Secure Cyberspace, Ruston, LA 71272 USA
来源：
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2010年 / 32卷 / 07期
关键词：
Feature selection; entropy; mutual information; Bayes classification error; entropy estimation; CLASSIFICATION;
D O I：
10.1109/TPAMI.2010.62
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We derive the feature selection criterion presented in [1] and [2] 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.
引用
收藏
页码：1342 / 1343
页数：2
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