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Lecture Notes for Chapter 2 Introduction to Data Mining

Attribute Type Description Examples Operations Nominal The values of a nominal attribute are just different names, i.e., nominal attributes provide only enough

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1 Introduction 1. Discuss whether or not each of the following activities is a data mining task. (a) Dividing the customers of a company according to their gender.

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Description. For courses in data mining and database systems. 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.

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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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Lecture Notes for Chapter 3 Introduction to Data Mining

© Tan,Steinbach, Kumar Introduction to Data Mining 8/05/2005 ‹#› Frequency and Mode The frequency of an attribute value is the

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Introduction 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 with basic concepts that provide necessary background for understanding each data mining technique, followed by more ...

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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.

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Pang-Ning Tan, Michael Steinbach and Vipin Kumar, Introduction to Data Mining, Addison Wesley, 2006 or 2017 edition. The examples are used in my data mining course at SMU and will be regularly updated and improved.

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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.

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It supplements the discussions in the other chapters with a discussion of the statistical concepts (statistical significance, p-values, false discovery rate, permutation testing, etc.) relevant to avoiding spurious results, and then illustrates these concepts in the context of data mining techniques.

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'Data Mining' presents fundamental concepts and algorithms for thos elearning 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.Pang-Ning Tan is the author of 'Introduction to Data Mining', published 2005 under ISBN 9780321321367 ...

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