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Avoiding False Discoveries: A completely new addition in the second edition is a chapter on how to avoid false discoveries and produce valid results, which is novel among other contemporary textbooks on data mining. It supplements the discussions in the other chapters with a discussion of the statistical concepts (statistical significance, p-values, false discovery rate, permutation testing ...

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PDF FULL Introduction to Data Mining PDF PDF FULL Introduction to Data Mining by by Pang-Ning Tan, Michael Steinbach, Vipin KumarIntroduction to Data Mining Presents fundamental concepts and algorithms for those learning data mining for the first time. This book explores each concept and features each major topic organized into two chapters ...

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Pang-Ning Tan, Michigan State University, Michael Steinbach, University of Minnesota Vipin Kumar, University of Minnesota Table of Contents Sample Chapters Resources for Instructors and Students Solution Manual Errata (March 25, 2006) Webpage for Second Edition (2018)

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expression data – scientific simulations generating terabytes of data • Traditional techniques infeasible for raw data • Data mining may help scientists – in classifying and segmenting data – in Hypothesis Formation Slide source: Tan, Steinbach, Kumar, Introduction to Datamining, Pearson Int’l Edition

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