Introduction to Data Mining, 2nd edition

Published by Pearson (July 14, 2021) © 2019

  • Pang-Ning Tan Michigan State University
  • Michael Steinbach University of Minnesota
  • Vipin Kumar University of Minnesota
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Introduction to Data Mining introduces the fundamental concepts and algorithms of data mining. The text offers 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 providing the reader with the necessary background for the application of data mining to real problems. The text helps you understand the nuances of the subject, and includes important sections on classification, association analysis and cluster analysis.

This 2nd Edition improves on the first iteration of the book, published over a decade ago, by addressing the significant changes in the industry as a result of advanced technology and data growth.

  1. Introduction
  2. Data
  3. Classification: Basic Concepts and Techniques
  4. Classification: Alternative Techniques
  5. Association Analysis: Basic Concepts and Algorithms
  6. Association Analysis: Advanced Concepts
  7. Cluster Analysis: Basic Concepts and Algorithms
  8. Cluster Analysis: Additional Issues and Algorithms
  9. Anomaly Detection
  10. Avoiding False Discoveries

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