Introduction to Data Mining, Global Edition, 2nd edition

Published by Pearson (March 4, 2019) © 2019

  • Pang-Ning Tan Michigan State University
  • Michael Steinbach University of Minnesota
  • Vipin Kumar University of Minnesota
  • Anuj Karpatne University of Minnesota
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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 organised into two chapters, beginning with basic concepts that provide necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.



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

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