Design of Support Vector Machine by adaptive aggregation

被引：0

作者：

Chacon, O ^{[1
]}

Litvintchev, I ^{[1
]}

Alvarez, A ^{[1
]}

Vazquez, E ^{[1
]}

机构：

[1] Univ Autonoma Nuevo Leon, Grad Program Elect Engn, Grad Program Syst Engn, San Nicolas De Los Garza 66450, Nuevo Leon, Mexico

来源：

PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4 | 2003年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article provides a new algorithm to solve the design of classification machine, for linearly separable sets, based in support vectors. For large scale binary classification, an adaptive aggregation (AAM) procedure is executed so that the size of possible support vectors decrease, in each iteration, until convergence to maximum separation margin is achieved.

引用

页码：2083 / 2087

页数：5

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