A consistent combined classification rule

被引：15
|
作者：
Mojirsheibani, M [1 ]
机构：
[1] CARLETON UNIV,DEPT MATH & STAT,OTTAWA,ON K1S 5B6,CANADA
来源：
STATISTICS & PROBABILITY LETTERS | 1997年 / 36卷 / 01期
关键词：
classification rule; Bayes classifier; linear classifier; misclassification error rate; shatter coefficient; consistency;
D O I：
10.1016/S0167-7152(97)00047-3
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this article we propose a data-based method for constructing combined classifiers. The resulting classifiers, which are linear in nature, turn out to be consistent. (C) 1997 Elsevier Science B.V.
引用
收藏
页码：43 / 47
页数：5
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