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计算机工程 ›› 2008, Vol. 34 ›› Issue (5): 57-59. doi: 10.3969/j.issn.1000-3428.2008.05.020

• 软件技术与数据库 • 上一篇    下一篇

基于关联规则的覆盖领域约简算法

吴 涛1, 2,尚 丽2,王 伟2,陈黎伟2   

  1. (1. 安徽大学智能计算与信号处理教育部重点实验室,合肥 230039;2. 安徽大学数学与计算科学学院,合肥 230039)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-03-05 发布日期:2008-03-05

Algorithm of the Covering Domains Reduction Based on Association Rule

WU Tao1, 2, SHANG Li2, WANG Wei2, CHEN Li-wei2   

  1. (1. Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education, Anhui University, Hefei 230039; 2. School of Mathematics and Computational Science , Anhui University, Hefei 230039)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-03-05 Published:2008-03-05

摘要: 前向神经网络的网络覆盖算法根据样本数据构造性地建立神经网络,其结构易于确定,执行效率高。但由于噪声数据的存在,可能造成覆盖领域多的现象,增加了网络结构的复杂度,并产生一些不必要的误识。该文借鉴数据挖掘中关联规则的支持度与可信度的概念,对覆盖领域进行约简,理论分析和实验表明,该算法可以有效地简化覆盖网络的结构,提高网络的稳定性和推广能力。

关键词: 神经网络, 覆盖领域, 约简

Abstract: As the covering algorithm of forward neural networks design the network according to the training samples, its framework is easy to define and its performance is high. But the existence of noise samples may lead to some small covering domains, and these small domains increase the complexity and result in misrecognition. The support and confidence of a covering domain are defined and an algorithm of domains reduction is presented in this paper. Experimental results show that this algorithm can simplify the structure of the covering network and improve the stability of networks.

Key words: neural networks, covering domain, reduction

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