Statistical themes and lessons for data mining

被引:102
作者
Glymour, C [1 ]
Madigan, D
Pregibon, D
Smyth, P
机构
[1] Carnegie Mellon Univ, Dept Cognit Psychol, Pittsburgh, PA 15213 USA
[2] Univ Washington, Dept Stat, Seattle, WA 98195 USA
[3] AT&T Bell Labs, Stat Res, Murray Hill, NJ 07974 USA
[4] Univ Calif Irvine, Irvine, CA 92717 USA
关键词
statistics; uncertainty; modeling; bias; variance;
D O I
10.1023/A:1009773905005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data mining is on the interface of Computer Science and Statistics, utilizing advances in both disciplines to make progress in extracting information from large databases. It is an emerging field that has attracted much attention in a very short period of time. This article highlights some statistical themes and lessons that are directly relevant to data mining and attempts to identify opportunities where close cooperation between the statistical and computational communities might reasonably provide synergy for further progress in data analysis.
引用
收藏
页码:11 / 28
页数:18
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