EVALUATION OF THE BRANCH AND BOUND ALGORITHM FOR FEATURE-SELECTION

被引：11

作者：

HAMAMOTO, Y ^{[1
]}

UCHIMURA, S ^{[1
]}

MATSUURA, Y ^{[1
]}

KANAOKA, T ^{[1
]}

TOMITA, S ^{[1
]}

机构：

[1] OSHIMA NATL COLL MARITIME TECHNOL, OSHIMA 74221, JAPAN

来源：

PATTERN RECOGNITION LETTERS | 1990年 / 11卷 / 07期

关键词：

bound algorithm; branch; exhaustive search algorithm; Feature selection; recognition rate;

D O I：

10.1016/0167-8655(90)90078-G

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Narendra and Fukunaga show that the branch and bound algorithm guarantees the optimal feature subset without evaluating all possible feature subsets, if the criterion function used satisfies the 'monotonicity' property. In this paper, we show that the algorithm works well in terms of the recognition rate, even if the property is not satisfied. © 1990.

引用

页码：453 / 456

页数：4

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