A Bahadur representation of the linear support vector machine

被引:0
|
作者
Koo, Ja-Yong [1 ]
Lee, Yoonkyung [2 ]
Kim, Yuwon [3 ]
Park, Changyi [4 ]
机构
[1] Korea Univ, Dept Stat, Seoul 136701, South Korea
[2] Ohio State Univ, Dept Stat, Columbus, OH 43210 USA
[3] NHN Inc, Data Min Team, Gyeonggi Do 463847, South Korea
[4] Univ Seoul, Dept Stat, Seoul 130743, South Korea
关键词
asymptotic normality; Bahadur representation; classification; convexity lemma; Radon transform;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The support vector machine has been successful in a variety of applications. Also on the theoretical front, statistical properties of the support vector machine have been studied quite extensively with a particular attention to its Bayes risk consistency under some conditions. In this paper, we study somewhat basic statistical properties of the support vector machine yet to be investigated, namely the asymptotic behavior of the coefficients of the linear support vector machine. A Bahadur type representation of the coefficients is established under appropriate conditions, and their asymptotic normality and statistical variability are derived on the basis of the representation. These asymptotic results do not only help further our understanding of the support vector machine, but also they can be useful for related statistical inferences.
引用
收藏
页码:1343 / 1368
页数:26
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