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Introduction to Data Mining, ISBN: 9780133128901 ...

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Introduction to Data Mining 2nd Edition by Pang-Ning Tan; Michael Steinbach; Anuj Karpatne; Vipin Kumar and Publisher Pearson. Save up to 80% by choosing the eTextbook option for ISBN: 9780134080284, 0134080289. The print version of this textbook is ISBN: 9780133128901, 0133128903.

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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 ...

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Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

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Introduction to Data Mining (First Edition) 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 ...

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Introduction to Data Mining, 2nd Edition, gives a comprehensive overview of the background and general themes of data mining and is designed to be useful to students, instructors, researchers, and professionals. Presented in a clear and accessible way, the book outlines fundamental concepts and ...

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– Introduction to Data Mining by Pang-Ning Tan, Michael Steinbach, and Vipin Kumar, 2003 – Data Mining: Concepts and Techniques by Jiawei Han and Micheline Kamber, 2000 . University of Florida CISE department Gator Engineering Data Mining Sanjay Ranka Spring 2011 Data Mining ...

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Aug 04, 2017· I have read several data mining books for teaching data mining, and as a data mining researcher. If you come from a computer science profile, the best one is in my opinion: "Introduction to Data Mining" by Tan, Steinbach and Kumar. It is a book th...

Introduction to Data Mining - University of Minnesota

Feb 14, 2018· 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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"Introduction to Data Mining is a complete introduction to data mining for students, researchers, and professionals. It provides a sound understanding of the foundations of data mining, in addition to covering many important advanced topics."--BOOK JACKET. xxi, 769 p. : ill. ; 24 cm. Mineração de dados. Recuperação da informação. Data mining.

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Editions for Introduction to Data Mining: 0321321367 (Hardcover published in 2005), 0133128903 (Hardcover published in 2018), 7115241007 (Paperback publi...

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Aug 06, 2008· 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 with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

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Quick-R Computing for Data Analysis (with R): a free online course Lecture slides (in both PPT and PDF formats) and three sample Chapters on classification, association and clustering available at the above link. Data Mining - Concepts and Techniques (3rd edition) by Jiawei Han, Micheline Kamber ...

9 Free Books for Learning Data Mining and Data Analysis

Apr 29, 2014· We are going to conclude our list of free books for learning data mining and data analysis, with a book that has been put together in nine chapters, and pretty much each chapter is written by someone else; but it all makes perfect sense together.

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We used this book in a class which was my first academic introduction to data mining. The book's strengths are that it does a good job covering the field as it was around the 2008-2009 timeframe. Included are discussions of exploring data, classification, clustering, association analysis, cluster analysis, and anomaly detection.

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Introducing the fundamental concepts and algorithms of data mining Introduction to Data Mining, 2nd Edition, gives a comprehensive overview of the background and general themes of data mining and is designed to be useful to students, instructors, researchers, and professionals. Presented in a clear and accessible way, the book outlines fundamental concepts and algorithms for each topic, thus ...