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文章基本信息

  • 标题:A comprehensive approach to mode clustering
  • 本地全文:下载
  • 作者:Yen-Chi Chen ; Christopher R. Genovese ; Larry Wasserman
  • 期刊名称:Electronic Journal of Statistics
  • 印刷版ISSN:1935-7524
  • 出版年度:2016
  • 卷号:10
  • 期号:1
  • 页码:210-241
  • DOI:10.1214/15-EJS1102
  • 语种:English
  • 出版社:Institute of Mathematical Statistics
  • 摘要:Mode clustering is a nonparametric method for clustering that defines clusters using the basins of attraction of a density estimator’s modes. We provide several enhancements to mode clustering: (i) a soft variant of cluster assignment, (ii) a measure of connectivity between clusters, (iii) a technique for choosing the bandwidth, (iv) a method for denoising small clusters, and (v) an approach to visualizing the clusters. Combining all these enhancements gives us a complete procedure for clustering in multivariate problems. We also compare mode clustering to other clustering methods in several examples.
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