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Data Mining
Hoofdkenmerken
Auteur: Ian H. Witten; Eibe Frank; Mark A. Hall; Christopher J. Pal
Titel: Data Mining
Uitgever: Elsevier S & T
ISBN: 9780128043578
ISBN boekversie: 9780128042915
Editie: 4
Prijs: € 52,74
Verschijningsdatum: 01-10-2016
Inhoudelijke kenmerken
Categorie: Data mining
Taal: English
Imprint: Morgan Kaufmann
Technische kenmerken
Verschijningsvorm: E-book
 

Inhoudsopgave:

\u003cp\u003e\u003ci\u003eData Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, \u003c/i\u003eoffers 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.\u003c/p\u003e \u003cp\u003eExtensive 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.\u003c/p\u003e \u003cp\u003ePlease visit the book companion website at https://www.cs.waikato.ac.nz/~ml/weka/book.html.\u003c/p\u003e \u003cp\u003eIt contains\u003c/p\u003e \u003cul\u003e \u003cli\u003ePowerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book\u003c/li\u003e \u003cli\u003eOnline Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book\u003c/li\u003e \u003cli\u003eTable of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.\u003c/li\u003e\u003c/ul\u003e\u003cul\u003e \u003cli\u003eProvides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects\u003c/li\u003e \u003cli\u003ePresents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods\u003c/li\u003e \u003cli\u003eIncludes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface\u003c/li\u003e \u003cli\u003eIncludes open-access online courses that introduce practical applications of the material in the book\u003c/li\u003e\u003c/ul\u003e
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