期刊文献+

基于聚类的比例规则

Ratio Rules Based on Clusters
下载PDF
导出
摘要 该文提出了基于聚类的比例规则(CRR),该规则保留了比例规则(RR)的优良特性,同时适用于多峰分布的数据集。实验证明,基于聚类的比例规则的预测效果优于比例规则的预测效果。 Ratio Rules based on clusters are proposed in this paper.They not only reserve the fine features of Ratio Rules,but also suit datasets which have many peaks.Experiments on two real datasets demonstrate that the proposed method achieves less root-mean-square than Ratio Rules.
出处 《计算机工程与应用》 CSCD 北大核心 2001年第14期115-117,173,共4页 Computer Engineering and Applications
基金 云南省自然科学基金资助
关键词 比例规则 数据挖掘 预测 基于聚类的比例规则 Ratio Rules(RR), Data Mining, Forecast, Ratio Rules based on clusters(CRR)
  • 相关文献

参考文献4

  • 1[1]Rakesh Agrawal ,Tomasz Imielinski,Arun Swami. Mining Association Rules between Sets of Items in Large Database[C].In Proc. Of the 1993ACM SIGMOD Conference,Washington D.C.,USA,1993.5:207-216
  • 2[2]Ramakrishnan Srikant,Rakesh Agrawal. Mining Quantitative Association Rules in Large Relational Tables[C]. In Proc. Of the 1996 ACM SIGMOD Conference,Montreal Quebec,Canada, 1996.6:1-12
  • 3[3]Flip Korn,Alexandors Labrinidis,Yannis Kotidis,Christos Faloutsos.Ratio Rules:A new paradigm for fast,Quantifiable data mining[C].In Proc.Of the 24th VLDB Conference,New York,USA,1998:582-593
  • 4周丽华,尤卫红.基于多元时间序列的Kn近邻预测模型[J].成都气象学院学报,1999,14(1):58-63. 被引量:2

二级参考文献5

共引文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部