Detecting group differences: Mining contrast sets

Detecting group differences: Mining contrast sets (2001)

by Stephen D. Bay , Michael J. Pazzani

Venue:	Data Mining and Knowledge Discovery
Citations:	61 - 3 self

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Datum	Value	Source
TITLE	Detecting group differences: Mining contrast sets	user correction
AUTHOR NAME	Stephen D. Bay	user correction
AUTHOR AFFIL	Department of Information and Computer Science; University of California, Irvine	user correction
AUTHOR ADDR	Irvine, CA 92697, USA	user correction
AUTHOR NAME	Michael J. Pazzani	user correction
AUTHOR AFFIL	Department of Information and Computer Science; University of California, Irvine	user correction
AUTHOR ADDR	Irvine, CA 92697, USA	user correction
ABSTRACT	A fundamental task in data analysis is understanding the differences between several con-trasting groups. These groups can represent different classes of objects, such as male or female students, or the same group over time, e.g. freshman students in 1993 through 1998. We present the problem of mining contrast sets: conjunctions of attributes and values that differ meaningfully in their distribution across groups. We provide a search algorithm for mining contrast sets with pruning rules that drastically reduce the computational complexity. Once the contrast sets are found, we post-process the results to present a subset that are surprising to the user given what we have already shown. We explicitly control the probability of Type I error (false positives) and guarantee a maximum error rate for the entire analysis by using Bonferroni corrections.	user correction
YEAR	2001	INFERENCE
VENUE	Data Mining and Knowledge Discovery	user correction
PAGES	5--3	INFERENCE
CITATIONS	50 found	ParsCit 1.0