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  • 标题:Meta-learning in Grid-based Data Mining Systems
  • 本地全文:下载
  • 作者:Moez Ben Haj Hmida ; Yahya Slimani
  • 期刊名称:International Journal of Computer Networks & Communications
  • 印刷版ISSN:0975-2293
  • 电子版ISSN:0974-9322
  • 出版年度:2010
  • 卷号:2
  • 期号:5
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:The Weka4GML framework has been designed to meet the requirements of distributed data mining. In this paper, we present the Weka4GML architecture based on WSRF technology for developing meta-learning methods to deal with datasets distributed among Data Grid. This framework extends the Weka toolkit to support distributed execution of data mining methods, like meta-learning. The architecture and the behaviour of the proposed framework are described in this paper. We also detail the different steps needed to execute a meta-learning process on a Globus environment. The framework has been discussed and compared to related works.
  • 关键词:Data mining; meta-learning; grid computing; distributed dataset; WSRF.
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