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应用科学学报 ›› 2012, Vol. 30 ›› Issue (4): 397-407.doi: 10.3969/j.issn.0255-8297.2012.04.012

• 计算机科学与应用 • 上一篇    下一篇

人工内分泌机制在最近邻规则约减中的应用

赵理1;2， 王磊1， 徐庆征1   

  1. 1. 西安理工大学计算机科学与工程学院，西安710048
    2. 石家庄职业技术学院信息工程系，石家庄050081
  • 收稿日期:2011-04-29 修回日期:2012-03-23 出版日期:2012-07-23 发布日期:2012-07-23
  • 作者简介:赵理，博士生，讲师，研究方向：进化计算、数据挖掘，E-mail: zhaoli_xaut@163.com；王磊，教授，博导，研究方向：自然计算、智能信息处理，E-mail: leiwang@xaut.edu.cn
  • 基金资助:

    国家自然科学基金(No.60873035，No.61073091)；陕西省自然科学基金(No.2010JM8028)；西安理工大学优秀博士学位论文研
    究基金(No.116-211102)资助

Nearest Neighbor Rule Condensation Algorithm Based on Artificial Endocrine System

ZHAO Li1;2, WANG Lei1, XU Qing-zheng1   

  1. 1. School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China
    2. Department of Information Engineering, Shijiazhuang Vocational Technology Institute,Shijiazhuang 050081, China
  • Received:2011-04-29 Revised:2012-03-23 Online:2012-07-23 Published:2012-07-23

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摘要：

当训练样本集规模过大时，最近邻分类规则约减过程是一个耗时的过程. 目前，常见的约减算法往往存
在计算成本过高、约减过程难于并行化等问题. 针对该问题，文中将人工内分泌机制引入到最近邻规则的约减过程
中，保留不同类规则边界上的边界规则，规则的约减规模通过晶格的粒度来设定. 该方法可以在分割–约减–合并框
架下获得较高的一致性约减子集，从而使规则的约减过程并行化，缩短约减时间. 用11 个不同的数据集进行仿真
实验的结果显示，该方法简单而有效，较好地解决了大样本集的约减问题.

关键词: 最近邻规则, 人工内分泌机制, 约减, 一致性子集

Abstract:

The main disadvantage in most prototype reduction algorithms is the excessive computational cost
especially when the prototype size is large. To deal with the problem, we present a new prototype reduction
method in which an artificial endocrine system is embedded. The method remains only for points on boundaries
between different classes. The amount of reduced rules of the reference set can be revised by granularity of
the lattice. The proposed method can get a consistent subset in a divide-reduce-coalesce manner, making it
more efficient and effective than other algorithms. The proposed approach has been tested using 11 different
datasets. The experiments show that the algorithm can give correct results when the size of dataset is large.

Key words: nearest neighbor rule, artificial endocrine system, condensation, consistent subset

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