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  • 标题:An Ensemble Method for Validation of Cluster Analysis
  • 本地全文:下载
  • 作者:Sunghae Jun
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2011
  • 卷号:8
  • 期号:6
  • 出版社:IJCSI Press
  • 摘要:Clustering is more subjective work than classification and regression. Though classification and regression have many general validation measures, clustering has few validation measures. Also, it is difficult to develop general measure of cluster validation. So, many evaluation measures have been published for cluster validation. In this paper, we propose an ensemble method of validation for cluster analysis. We use voting approach to some validation measures of cluster analysis. To verify our improved performance, we make experiments by some objective data sets from UCI machine learning repository.
  • 关键词:Cluster Analysis; Cluster Validation; Ensemble Method; Voting; Internal measures; Stability measures
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