期刊文献+

最小二乘法解决关联规则相关性的研究

Research on Least Square Solution Correlation of Association Rules
下载PDF
导出
摘要 数据挖掘中的关联规则是一个重要研究领域和研究方向,决策者根据挖掘得到的分析结果是数据挖掘的最终目标,使商业计策趋优,从而提高企业利润。文章提出了数据挖掘与最优化方法的完美结合,从而构造出一种决策分析问题求解的模型,将最优化方法与数据挖掘技术在问题求解实例中合理地结合,能够达到最终理想结果,为疑难杂症等的问题的求解和决策提供一个实施可行的参考模型和方法。 The association rules in data mining is an important research area and research directions, policy makers based on mining the results is the ultimate goal of data mining, and business strategy, thus raising profits.Data mining and optimization method is proposed in this paper the perfect combination, so as to construct a decision analysis model of problem solving, optimization and data mining technology in the problem solving examples of reasonable combination can achieve the desired results, for incurable diseases, such as problem solving and decision to provide a reference model and method of implementing viable.
作者 邢泽欣
机构地区 石家庄经济学院
出处 《无线互联科技》 2015年第23期116-118,共3页 Wireless Internet Technology
关键词 最小二乘法 线性回归 反向验证 关联规则 相关性 least square method linear regression: backward verification association rule correlation
  • 相关文献

参考文献11

二级参考文献25

  • 1[1]Agrawal R.Srikant R.Fast Algorithm for Mining Association Rules.lnProcccdings of the 20th VLDB Confercnec . Santigo . Chile, 1994 被引量:1
  • 2[2]Srikant R,Agrawal RMining Generalized Association RuleslnProcccdings of the 21st VLDB Conference Zurich, Switzerland. 1995 被引量:1
  • 3[3]Agrawal R,Imiclinski T,Swami A Mining Association Rules between Sctsof ltems in Large Databases Procccdings of the 1993 ACM SIGMODConfercnec, Washington DC, USA, 1993-05 被引量:1
  • 4[4]Brin S,Motwani R,Silverstein CBeyond Market Baskets:GcncralizingAssociation Rules to Corrclations. Procccdings of the 1997 ACMSIGMOD Conferencc on Management of Data. pages 265-276 , Tucson ,AZ, 1997-05:256-276 被引量:1
  • 5[5]Fayyad UM,Piatctsky-shapiro GSmyth P Knowledge Discovcry and DataMining:Towards a Unifying Framcwork Proeof the 2meInt.Confer. Knowledgc Discovery and Data Mining (KDD-96).Portland.1996 被引量:1
  • 6Carlin B.P.,Louis T.A..Bayes and Empirical Bayes Methods for Data Analysis.2nd Edition.London U.K.:Chapman &Hall,2000 被引量:1
  • 7Light R.J.,Margolin B.H..An analysis of variance for categorical data.Journal of the American Statistical Association,1971,66:534~544 被引量:1
  • 8Steven R.,Matthew S.etal.Integrated Public Use Microdata Series:Version 2.0.Historical Census Projects,University of Minnesota,Minneapolis,1997 被引量:1
  • 9Au W.-H.,Chan K.C.C.,Yao X..A novel evolutionary data mining algorithm with applications to churn prediction.IEEE Transactions on Evolutionary Computation,2003,7 (6):532~545 被引量:1
  • 10http://fuzzy.cs.uni-magdeburg.de/~borgelt,2004年5月9日. 被引量:1

共引文献87

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