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  • 标题:Preprocessor Agent Approach to Knowledge Discovery Using Zero-R Algorithm
  • 本地全文:下载
  • 作者:Inamdar S A ; Narangale S.M. ; G. N. Shinde
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2011
  • 卷号:2
  • 期号:12
  • DOI:10.14569/IJACSA.2011.021212
  • 出版社:Science and Information Society (SAI)
  • 摘要:Data mining and multiagent approach has been used successfully in the development of large complex systems. Agents are used to perform some action or activity on behalf of a user of a computer system. The study proposes an agent based algorithm PrePZero-r using Zero-R algorithm in Weka. Algorithms are powerful technique for solution of various combinatorial or optimization problems. Zero-R is a simple and trivial classifier, but it gives a lower bound on the performance of a given dataset which should be significantly improved by more complex classifiers. The Proposed Algorithm called PrePZero-r has significantly reduced time taken to build the model than Zero-R algorithm by removing the Lower Bound Values 0 while preprocessing and comparing the result with class values. Also proposed study introduced new factor “Accuracy (1-e)” for each individual attribute.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; Data mining; Zero-R algorithm; Lower Bound Value; Class values.
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