Introduction to Data Mining (GE)

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 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.

作者：Pang-Ning Tan
現職：Michigan State University

作者：Michael Steinbach
現職：University of Minnesota

作者：Anuj Karpatne
現職：University of Minnesota

作者：Vipin Kumar
現職：University of Minnesota

Ch 1 Introduction
Ch 2 Data
Ch 3 Classification: Basic Concepts and Techniques
Ch 4 Association Analysis: Basic Concepts and Algorithms
Ch 5 Cluster Analysis: Basic Concepts and Algorithms
Ch 6 Classification: Alternative Techniques
Ch 7 Association Analysis: Advanced Concepts
Ch 8 Cluster Analysis: Additional Issues and Algorithms
Ch 9 Anomaly Detection
Ch10 Avoiding False Discoveries