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Introduction to data mining /

By: Tan, Pang-Nin
Title By: Steinbach, Michael | Kumar, Vipin, 1956-
Series: Pearson custom library.Publisher: Essex : Pearson, c2014.Edition: Pearson new international edition.Description: ii, 732 p. : ill. ; 28 cm.ISBN: 9781292026152Program: INFO911Subject(s): Data miningDDC classification: 006.312 TA IN Online resources: Ebook | Location Map
Summary:
Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide the necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.
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Item type Home library Call number url Status Notes Date due Barcode Item holds Course reserves
CRS University of Wollongong in Dubai
Closed Reserve
006.312 TA IN (Browse shelf) link Available T0060363

INFO911 Autumn2021

REGULAR University of Wollongong in Dubai
Main Collection
006.312 TA IN (Browse shelf) Available T0060364
3 DAY LOAN University of Wollongong in Dubai
Main Collection
006.312 TA IN (Browse shelf) Available Oct2018 T0060365
Total holds: 0

Originally published by Pearson Addison Wesley, c2006.
"This is a special adaptation of an established title widely used by colleges and universities throughout the world."--Back cover.
Includes bibliographical references and index.

Chapter 1. Introduction --
Chapter 2. Data --
Chapter 3. Exploring Data --
Chapter 4. Classification: Basic Concepts, Decision Trees, and Model Evaluation --
Chapter 5. Classification: Alternative Techniques --
Chapter 6. Association Analysis: Basic Concepts and Algorithms --
Chapter 7. Association Analysis: Advanced Concepts --
Chapter 8. Cluster Analysis: Basic Concepts and Algorithms --
Chapter 9. Cluster Analysis: Additional Issues and Algorithms --
Chapter 10. Anomaly Detection

Introduction to Data Mining presents fundamental concepts and algorithms for those learning data mining for the first time. Each major topic is organized into two chapters, beginning with basic concepts that provide the necessary background for understanding each data mining technique, followed by more advanced concepts and algorithms.

INFO911

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