Introduction to data mining

by Tan, Pang-Ning

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Title Statements

Full title :Introduction to data mining / Pang-Ning Tan, Michigan State University, Michael Steinbach, University of Minnesota, Anuj Karpatne, University of Minnesota, Vipin Kumar, University of Minnesota

Summary

Introducing the fundamental concepts and algorithms of data mining Introduction to Data Mining, 2nd Edition, gives 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 readers understand the nuances of the subject, and includes important sections on classification, association analysis, and cluster analysis. This 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

Edition Statements

Publication Date:2019
Edition:Second edition

Publication Statements

Publisher(s):Pearson
Place of Publication:NY NY
Language:eng
Publication Date:2019

Notes

Brief Contents Introduction Data Classification: Basic Concepts and Techniques Classification: Alternative Techniques Association Analysis: Basic Concepts and Algorithms Association Analysis: Advanced Concepts Cluster Analysis: Basic Concepts and Algorithms Cluster Analysis: Additional Issues and Algorithms Anomaly Detection Avoiding False Discoveries