A Critical View on Automatic Significance-Filtering in Pattern Mining

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Florian Lemmerich, Frank Puppe ;
Proceedings of the Workshop on Statistically Sound Data Mining at ECML/PKDD, PMLR 47:21-27, 2015.

Abstract

Statistically sound validation of results plays an important role in modern data mining. In this context, it has been advocated to disregard patterns that cannot be automatically confirmed as statistically valid by the available data. In this short position paper, we argue against a mandatory automatic significance filtering of results.

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