Support vector machines as Bayes? classifiers

被引：3

作者：

Jackson, Peter L. ^{[1
]}

机构：

[1] Singapore Univ Technol & Design, 8 Somapah Rd, Singapore 487372, Singapore

来源：

OPERATIONS RESEARCH LETTERS | 2022年 / 50卷 / 05期

关键词：

Support vector machines; Na?ve Bayes? classifier; Multi-class classification;

D O I：

10.1016/j.orl.2022.06.003

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

We reformulate the problem of determining support vectors directly as an application of Bayes' classifiers rather than as the dual program to a binary geometric separation problem. The primary purpose of the reformulation is to create a simpler exposition of the support vector machines technique. A secondary advantage is that it immediately and naturally applies to multi-class classification problems where the kernel function can be normalized as a density.

引用

页码：423 / 429

页数：7