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  • 标题:FORWARD REGRESSION IN R: FROM THE EXTREME SLOW TO THE EXTREME FAST
  • 本地全文:下载
  • 作者:Michail Tsagris ; Manos Papadakis
  • 期刊名称:Journal of Data Science
  • 印刷版ISSN:1680-743X
  • 电子版ISSN:1683-8602
  • 出版年度:2018
  • 卷号:16
  • 期号:4
  • 页码:771-780
  • DOI:10.6339/JDS.201810_16(4).00006
  • 出版社:Tingmao Publish Company
  • 摘要:Forward regression has been criticised heavily and one of the many reasons is regarding its speed and its stopping criteria. The main focus of this paper is on demonstrating how to make it efficient, using R. Our method worksfor continuous predictor variables only, as the use of the partial correlation plays the most important role..
  • 关键词:forward regression; partial correlation coefficient; computational efficiency
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