Data snooping, dredging and fishing

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Data snooping, dredging and fishing: the dark side of data mining a SIGKDD99 panel report

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ACM SIGKDD Explorations Newsletter archive
Volume 1 , Issue 2 (January 2000) table of contents

COLUMN: KDD-99 conference reports table of contents

Pages: 52 - 54

Year of Publication: 2000

ISSN:1931-0145

Author

David Jensen

University of Massachusetts, Amherst, MA

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 3, Downloads (12 Months): 15, Citation Count: 3

Additional Information:

abstract references cited by index terms collaborative colleagues

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ABSTRACT

This article briefly describes a panel discussion at SIGKDD99.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Eibe Frank , Ian H. Witten, Using a Permutation Test for Attribute Selection in Decision Trees, Proceedings of the Fifteenth International Conference on Machine Learning, p.152-160, July 24-27, 1998
	2	Y. Hochberg , A. C. Tamhane, Multiple comparison procedures, John Wiley & Sons, Inc., New York, NY, 1987
	3	David Donald Jensen, Induction with randomization testing: decision-oriented analysis of large data sets, Washington University, St. Louis, MO, 1992
	4	David D. Jensen , Paul R. Cohen, Multiple Comparisons in Induction Algorithms, Machine Learning, v.38 n.3, p.309-338, March 2000 [doi>10.1023/A:1007631014630]
	5	Leamer, E. Specification Searches: Ad Hoc Inference with Nonexperimental Data. Wiley. 1978
	6	Malkiel, B. A Random Walk Down Wall Street. Norton. 1996.
	7	Oates, T. and D. Jensen. Large datasets lead to overly complex models: An explanation and a solution. In Proceedings of The Fourth International Conference on Knowledge Discovery and Data Mining. 1998. 294--298. http://www-eksl.cs.umass.edu/papers/oates-kdd98-Datasets.ps
	8	Sullivan, R., A. Timmermann, and H. White. Data-snooping, technical trading rule performance, and the bootstrap. UCSD Department of Economics Discussion Paper #97-31. December 1997. ftp://weber.ucsd.edu/pub/econlib/dpapers/ucsd9731.ps.gz
	9	Sullivan, R., A. Timmermann, and H. White. Dangers of data-driven inference: The case of calendar effects in stock returns. UCSD Department of Economics Discussion Paper #98-16. June 1998. http://weber.ucsd,edu/Depts/Econ/Wpapers/Files/ucsd9816.pdf
	10	Westfall, P. and S. Young, Resampling-Based Multiple Testing. Wiley. 1993
	11	White, H. A Reality Check for Data Snooping. QRDA, LLC Technical Report #98-01. May 1997.

CITED BY 3

	John Wang , Alan Oppenheim, The pitfalls of knowledge discovery in databases and data mining, Data mining: opportunities and challenges, Idea Group Publishing, Hershey, PA, 2003
	Jessica Lin , Eamonn Keogh , Wagner Truppel, Clustering of streaming time series is meaningless, Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery, June 13-13, 2003, San Diego, California
	John Wang , Xiaohua Hu , Dan Zhu, Diminishing downsides of Data Mining, International Journal of Business Intelligence and Data Mining, v.2 n.2, p.177-196, June 2007

INDEX TERMS

Keywords:
SIGKDD99, overfitting, panels

Collaborative Colleagues:

David Jensen: colleagues

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