Statistical Themes and Lessons for Data Mining

被引：0
|
作者：
Clark Glymour
David Madigan
Daryl Pregibon
Padhraic Smyth
机构：
[1] Carnegie Mellon University,Department of Cognitive Psychology
[2] University of Washington,Department of Statistics
[3] Statistics Research,AT&T Laboratories
[4] University of California,Information and Computer Science
来源：
Data Mining and Knowledge Discovery | 1997年 / 1卷
关键词：
statistics; uncertainty; modeling; bias; variance;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Data mining is on the interface of Computer Science andStatistics, utilizing advances in both disciplines to make progressin extracting information from large databases. It is an emergingfield that has attracted much attention in a very short period oftime. This article highlights some statistical themes and lessonsthat are directly relevant to data mining and attempts to identifyopportunities where close cooperation between the statistical andcomputational communities might reasonably provide synergy forfurther progress in data analysis.
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页码：11 / 28
页数：17
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