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Controlling False Positives in Association Rule Mining

Summary: Controls false positives in association-rule mining by applying three multiple-testing corrections: direct adjustment, permutation-based, and holdout. Finds many spurious rules without correction; permutation-based approach offers strongest power but is expensive, with cost-reduction techniques proposed. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10383
Venue
VLDB
Year
2012
Pagerank
4.1905499e-05
Overall Rank
12,140 | 15.63%
DOI
-

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