具体描述
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.
著者信息
作者简介
Pang-Ning Tan
现职：Michigan State University
Michael Steinbach
现职：University of Minnesota
Anuj Karpatne
现职：University of Minnesota
Vipin Kumar
现职：University of Minnesota
Pang-Ning Tan
现职：Michigan State University
Michael Steinbach
现职：University of Minnesota
Anuj Karpatne
现职：University of Minnesota
Vipin Kumar
现职：University of Minnesota
图书目录
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
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
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