Data mining : practical machine learning tools and techniques /
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaime...
| Main Authors: | , , , |
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| Corporate Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Cambridge, MA, United States :
Morgan Kaufmann,
[2017]
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| Edition: | Fourth edition |
| Series: | Morgan Kaufmann series in data management systems.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at https://www.cs.waikato.ac.nz/~ml/weka/book.html. |
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| Physical Description: | 1 online resource (xxxii, 621 pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 573-600) and index |
| ISBN: | 9780128043578 0128043571 |