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计算机工程 ›› 2007, Vol. 33 ›› Issue (11): 209-212. doi: 10.3969/j.issn.1000-3428.2007.11.076

• 人工智能及识别技术 • 上一篇    下一篇

基于海量样本的模糊分类系统的设计

刘华富1,张文生2   

  1. (1. 长沙大学计算机科学与技术系,长沙 410003;2. 中国科学院自动化研究所,北京 100080)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2007-06-05 发布日期:2007-06-05

Design of Fuzzy Classification System Based on Massive Sample

LIU Huafu1, ZHANG Wensheng2   

  1. (1. Department of Computer Science & Technology, Changsha University, Changsha 410003; 2. Institute of Automation, Chinese Academy of Sciences, Beijing 100080)
  • Received:1900-01-01 Revised:1900-01-01 Online:2007-06-05 Published:2007-06-05

摘要: 使用支持向量机理论直接求海量数据的模糊分类系统是比较困难的。为了解决这个问题,该文提出了基于邻域原理计算支持向量,利用支持向量求出分类超平面,再设计模糊分类系统的方法。实验结果表明,该方法可以有效地解决对海量数据的模糊分类系统的设计 问题。

关键词: 邻域原理, 支持向量, 模糊分类系统

Abstract: It is rather difficult to design a fuzzy massive data classification system by using support vector machine directly. To solve this problem, fuzzy classification system is proposed by computing support vector based on neighborhood theory, and by obtaining classification hyper plane using support vector. The result of experiment shows the problem in designing fuzzy massive data classification system can be effectively solved by this method.

Key words: Neighborhood theory, Support vector, Fuzzy classification system

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