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Data Mining Concepts and Techniques (3rd ed.)

Table of Contents Cover Image Front Matter Copyright Dedication Foreword Foreword to Second Edition Preface Acknowledgments About the Authors 1. Introduction Why data Mining ? What Is data Mining ? What Kinds of data Can Be Mined? What Kinds of Patterns Can Be Mined? Which Technologies Are Used? Which Kinds of Applications Are Targeted? Major Issues in data Mining Summary Exercises Bibliographic Notes 2. Getting to Know Your data data Objects and Attribute Types Basic Statistical Descriptions of data data Visualization Measuring data Similarity and Dissimilarity Summary Exercises Bibliographic Notes 3.

Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations, 3rd Edition Ian Witten, Eibe Frank, Mark A. Hall Joe Celko's Data and Databases: Concepts in Practice Joe Celko Developing Time-Oriented Database Applications in …

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