Data Mining : Practical Machine Learning Tools and Techniques

Frank, Eibe, Hall, Mark A., Witten, Ian H.

ISBN 10: 0123748569 ISBN 13: 9780123748560
Published by Elsevier Science & Technology, 2011
Used Soft cover

From Better World Books, Mishawaka, IN, U.S.A. Seller rating 5 out of 5 stars 5-star rating, Learn more about seller ratings

AbeBooks Seller since 3 August 2006

This specific item is no longer available.

About this Item

Description:

Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Seller Inventory # 4268742-6

Report this item

Synopsis:

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research.

About the Author: Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand. He has published widely on digital libraries, machine learning, text compression, hypertext, speech synthesis and signal processing, and computer typography. He has written several books, the latest being Managing Gigabytes (1999) and Data Mining (2000), both from Morgan Kaufmann.

"About this title" may belong to another edition of this title.

Bibliographic Details

Title: Data Mining : Practical Machine Learning ...
Publisher: Elsevier Science & Technology
Publication Date: 2011
Binding: Soft cover
Condition: Good
Edition: 3rd Edition.

Top Search Results from the AbeBooks Marketplace

There are 7 more copies of this book

View all search results for this book