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Provides both theoretical and practical coverage of all data mining topics. Includes extensive number of integrated examples and figures. Offers instructor resources including solutions for exercises and complete set of lecture slides. Assumes only a modest statistics or mathematics background, and no database knowledge is needed.

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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, beginning

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Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary

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Jiawei Han and Micheline Kamber, “Data Mining: Concepts and Techniques”, Second Edition, 2006 ! Pang-Ning Tan, Michael Steinbach, and Vipin Kumar, "Introduction to Data Mining", Pearson Addison Wesley, 2008, ISBN: 0-32-134136-7. Project ! During Lab hours ! The project will be divided into small tasks, a new task every week ! The project can be done individually !

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Introduction to Data Mining, Second Edition, is intended for use in the Data Mining course. It is also suitable for individuals seeking an introduction to data mining. The text assumes only a modest statistics or mathematics background, and no database knowledge is needed. Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time.

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Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each concept is explored thoroughly and supported with numerous examples. The text requires only a modest background in mathematics. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each ...

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Chapter 8,9 from the book “Introduction to Data Mining” by Tan, Steinbach, Kumar. Lecture 8 a: Clustering Validity, Minimum Description Length (MDL), Introduction to Information Theory, Co-clustering using MDL. (ppt, pdf)

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