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  • 标题:Statistical Classification Using the Maximum Function
  • 本地全文:下载
  • 作者:T. Pham-Gia ; Nguyen D. Nhat ; Nguyen V. Phong
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2015
  • 卷号:05
  • 期号:07
  • 页码:665-679
  • DOI:10.4236/ojs.2015.57068
  • 语种:English
  • 出版社:Scientific Research Publishing
  • 摘要:The maximum of k numerical functions defined on , , by , is used here in Statistical classification. Previously, it has been used in Statistical Discrimination [1] and in Clustering [2]. We present first some theoretical results on this function, and then its application in classification using a computer program we have developed. This approach leads to clear decisions, even in cases where the extension to several classes of Fisher’s linear discriminant function fails to be effective.
  • 关键词:Maximum;Discriminant Function;Pattern Classification;Normal Distribution;Bayes Error;L1-Norm;Linear;Quadratic;Space Curves
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