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.
引用
收藏
页码：11 / 28
页数：17
相关论文
共 50 条
  • [1] Statistical themes and lessons for data mining
    Glymour, C
    Madigan, D
    Pregibon, D
    Smyth, P
    DATA MINING AND KNOWLEDGE DISCOVERY, 1997, 1 (01) : 11 - 28
  • [2] Themes in data mining, big data, and crime analytics
    Oatley, Giles C.
    WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2022, 12 (02)
  • [3] Statistical data mining
    Banks, David L.
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS, 2010, 2 (01): : 9 - 25
  • [4] Statistical models for data mining
    Giudici, P
    Heckerman, D
    Whittaker, J
    DATA MINING AND KNOWLEDGE DISCOVERY, 2001, 5 (03) : 163 - 165
  • [5] Statistical inference and data mining
    Glymour, C
    Madigan, D
    Pregibon, D
    Smyth, P
    COMMUNICATIONS OF THE ACM, 1996, 39 (11) : 35 - 41
  • [6] Statistical Models for Data Mining
    Paolo Giudici
    David Heckerman
    Joe Whittaker
    Data Mining and Knowledge Discovery, 2001, 5 : 163 - 165
  • [7] A statistical perspective on data mining
    Hosking, JRM
    Pednault, EPD
    Sudan, M
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 1997, 13 (2-3): : 117 - 134
  • [8] Statistical perspective on data mining
    IBM T.J. Watson Research Cent, Yorktown Heights, United States
    Future Gener Comput Syst, 2-3 (117-134):
  • [9] Editorial: Data mining lessons learned
    Lavrac, N
    Motoda, H
    Fawcett, T
    MACHINE LEARNING, 2004, 57 (1-2) : 5 - 11
  • [10] Editorial: Data Mining Lessons Learned
    Nada Lavrač
    Hiroshi Motoda
    Tom Fawcett
    Machine Learning, 2004, 57 : 5 - 11
12345