Finding the real patterns

Authors:
Geoffrey Webb
Affiliations:
Clayton School of Information Technology, Monash University, Victoria, Australia
Venue:
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2007

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Discovering significant rules

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Discovering significant patterns

Machine Learning

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Abstract

Pattern discovery is one of the fundamental tasks in data mining. Pattern discovery typically explores a massive space of potential patterns to identify those that satisfy some user-specified criteria. This process entails a huge risk (in many cases a near certainty) that many patterns will be false discoveries. These are patterns that satisfy the specified criteria with respect to the sample data but do not satisfy those criteria with respect to the population from which those data are drawn. This talk discusses the problem of false discoveries, and presents techniques for avoiding them.