Finding the real patterns

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. © Springer-Verlag Berlin Heidelberg 2007.