• Complex
  • Title
  • Keyword
  • Abstract
  • Scholars
  • Journal
  • ISSN
  • Conference
成果搜索

author:

孙昌儿 (孙昌儿.) [1] | 刘秉瀚 (刘秉瀚.) [2] (Scholars:刘秉瀚)

Indexed by:

CQVIP PKU CSCD

Abstract:

SVM在小训练样本、高维情况下具有很好的泛化性能,但它不适用于多类分类.本文分析基本的SVM和多类SVM分类器,重点讨论了SVM决策树,提出了一种结点分类器类集合划分方案来构造SVM决策树.实验结果表明,以这种方法构造的SVM决策树分类器分类性能较好.

Keyword:

SVM决策树 分类器 支持向量机

Community:

  • [ 1 ] [孙昌儿]福州大学
  • [ 2 ] [刘秉瀚]福州大学

Reprint 's Address:

Email:

Show more details

Version:

Related Keywords:

Related Article:

Source :

福州大学学报(自然科学版)

ISSN: 1000-2243

CN: 35-1337/N

Year: 2007

Issue: 3

Volume: 35

Page: 361-364

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

Online/Total:157/10050452
Address:FZU Library(No.2 Xuyuan Road, Fuzhou, Fujian, PRC Post Code:350116) Contact Us:0591-22865326
Copyright:FZU Library Technical Support:Beijing Aegean Software Co., Ltd. 闽ICP备05005463号-1