4.5 Article Proceedings Paper

On combining classifiers using sum and product rules

期刊

PATTERN RECOGNITION LETTERS
卷 22, 期 12, 页码 1283-1289

出版社

ELSEVIER
DOI: 10.1016/S0167-8655(01)00073-3

关键词

classification; combining classifiers; classifier fusion; k nearest-neighbours; neural networks

向作者/读者索取更多资源

This paper presents a comparative study of the performance of arithmetic and geometric means as rules to combine multiple classifiers. For problems with two classes., we prove that these combination rules are equivalent when using two classifiers and the sum of the estimates of the a posteriori probabilities is equal to one. We also prove that the case of a two class problem and a combination of two classifiers is the only one where such equivalence occurs. We present experiments illustrating the equivalence of the rules under the above mentioned assumptions. (C) 2001 Elsevier Science B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据