Introduction to data mining /
By: Tan, Pang-Nin
Title By: Steinbach, Michael | Kumar, Vipin
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 MapItem type | Home library | Call number | url | Status | Notes | Date due | Barcode | Item holds |
---|---|---|---|---|---|---|---|---|
REGULAR | University of Wollongong in Dubai Main Collection | 006.312 TA IN (Browse shelf) | link | Checked out | 05/06/2024 | T0060363 | ||
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 |
, Shelving location: Main Collection Close shelf browser
006.312 RO DA Data mining with decision trees : | 006.312 RO DA Data science and analytics with Python | 006.312 RU MI Mining the social web | 006.312 TA IN Introduction to data mining / | 006.312 TA IN Introduction to data mining / | 006.312 TA IN Introduction to data mining / | 006.312 TO DA Data mining with R : |
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