Computer Engineering and Applications ›› 2006, Vol. 42 ›› Issue (19): 14-16.

• 博士论坛 • Previous Articles     Next Articles

Data Classification Modeling Based on Granular Computing

PingAn Gao,ZiXing Cai,   

  1. 湘潭大学计算机科学系
  • Received:2006-04-12 Revised:1900-01-01 Online:2006-07-01 Published:2006-07-01
  • Contact: PingAn Gao



  1. 湘潭大学计算机科学系
  • 通讯作者: 高平安 gaopa gaopa

Abstract: Data classification modeling is studied based on Granular Computing. By using complete granularity space, a data set is expressed in granular forms, concept learning is rationally explained by granular computing theory, and then a KDD model based on data classification is educed. It concludes that KDD is to find an optimal granularity expression for an object concept, and the premise of decision rule is the disjunction of the granularities.

Key words: Data Classification Modeling, Granular Computing, Complete Granularity Space, Concept Learning

摘要: 本文研究基于粒度计算理论的数据分类建模,引入全粒度空间的概念,定出了集合的粒度表示,给出了概念学习在粒度计算理论中的解释,导出了一个基于数据分类的知识发现模型,从而说明知识发现可归结为在全粒度空间中寻找目标概念的最佳粒度表示,而各粒度描述的析取构成决策规则的前件。

关键词: 数据分类建模, 粒度计算, 全粒度空间, 概念学习