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  • 标题:A New Method for Generating All Positive and Negative Association Rules
  • 本地全文:下载
  • 作者:Rupesh Dewang ; Jitendra Agarwal
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2011
  • 卷号:3
  • 期号:04
  • 页码:1649-1657
  • 出版社:Engg Journals Publications
  • 摘要:Association Rule play very important role in recent scenario of data mining. But we have only generated positive rule, negative rule also useful in today data mining task. In this paper we are proposing �A new method for generating all positive and negative Association Rules� (NRGA).NRGA generates all association rules which are hidden when we have applied Apriori Algorithm. For representation of Negative Rules we are giving new name of this rules as like: CNR, ANR, and ACNR. In this paper we are also modify Correlation coefficient (CRC) equation, so all generate results are very promising. First we apply Apriori Algorithm for frequent itemset generation and that is also generate positive rules, after on frequent itemset we apply NRGA algorithm for all negative rules generation and optimize generated rules using Genetic Algorithm
  • 关键词:Association Rule; Data Mining; Genetic Algorithm; Negative Rules Generating Algorithm (NRGA).
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