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

页码：1342 / 1343

页数：2

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