Data mining : practical machine learning tools and techniques

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

"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. It provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects. It offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods. It includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks-in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization.

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この本の情報

書名 Data mining : practical machine learning tools and techniques
著作者等 Frank, Eibe
Witten, I. H.
Holmes Geoffrey
Witten Ian H.
Hall Mark A.
出版元 Elsevier;Morgan Kaufmann
刊行年月 c2011
版表示 3rd ed
ページ数 xxxiii, 629 p.
大きさ 24 cm
ISBN 9780123748560
NCID BB05016847
※クリックでCiNii Booksを表示
言語 英語
出版国 オランダ
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