%0 Journal Article %A Glymour, Clark %A Madigan, David %A Pregibon, Daryl %A Smyth, Padhraic %D 1997 %T Statistical Themes and Lessons for Data Mining %U https://kilthub.cmu.edu/articles/journal_contribution/Statistical_Themes_and_Lessons_for_Data_Mining/6492713 %R 10.1184/R1/6492713.v1 %2 https://kilthub.cmu.edu/ndownloader/files/11937314 %K statistics %K uncertainty %K modeling %K bias %K variance %X Data mining is on the interface of Computer Science and Statistics, utilizing advances in both disciplines to make progress in extracting information from large databases. It is an emerging field that has attracted much attention in a very short period of time. This article highlights some statistical themes and lessons that are directly relevant to data mining and attempts to identify opportunities where close cooperation between the statistical and computational communities might reasonably provide synergy for further progress in data analysis. %I Carnegie Mellon University