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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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Contents Preface to the Second Edition v 1 Introduction 1 1 1 What Is Data Mining 4 1 2 Motivating Challenges 5 1 3 The Origins of Data Mining 7 1 4 Data Mining Tasks 9 1 5 Scope and Organization of the Book 13 1 6 Bibliographic Notes 15 1 7 Exercises 21 2 Data 23 2 1 Types of Data 26 2 1 1 Attributes and Measurement 27

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Data mining techniques can be used to support a wide range of business intelligence applications such as customer profiling targeted marketing workflow management store layout and fraud detection It can also help retailers From Chapter 1 of Introduction to Data Mining First Edition Pang Ning Tan Michael Steinbach Vipin Kumar

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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 Presented in a clear and accessible way the book outlines

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The second edition of a highly praised successful reference on data mining with thorough coverage of big data applications predictive analytics and statistical analysis Includes new chapters on Multivariate Statistics Preparing to Model the Data and Imputation of Missing Data and an Appendix on Data Summarization and Visualization

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