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  • 标题:Classic and Modern in Regression Modelling
  • 本地全文:下载
  • 作者:Cristian Marinoiu
  • 期刊名称:Petroleum-Gas University of Ploiesti Bulletin : Economic Sciences Series
  • 印刷版ISSN:2284-8576
  • 电子版ISSN:2247-8582
  • 出版年度:2017
  • 期号:1
  • 语种:English
  • 出版社:Petroleum-Gas University of Ploiesti
  • 摘要:Regression models are one of the most important sections of the classical mathematical statistics,theoretical results obtained in this area are truly impressive.At the same time,their area of applicability is very wide.It is a much known fact that technical and economic sciences,sociology,biology,psychology,genetics are just a few examples that benefit from the advantages of the regression modelling.In this paper we review some layouts of machine learning inspired by the regression modelling with the intention of highlighting the extraordinary contribution of this concept of mathematical statistics and creating one of the most interesting branches of modern computer science,called data science.
  • 关键词:regression;regularization;Ridge regression;LASSO;elasticNet;PCR;PLS
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