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Data Mining: Practical Machine Learning Tools and

Data Mining: Practical Machine Learning Tools and

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) by Ian H. Witten, Eibe Frank, Mark A. Hall

Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems)



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Data Mining: Practical Machine Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in Data Management Systems) Ian H. Witten, Eibe Frank, Mark A. Hall ebook
Publisher: Morgan Kaufmann
ISBN: 0123748569, 9780123748560
Format: pdf
Page: 665


Xiaodong He 2008-10-07 22:20 Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems) by: Ian H. 075065757X Programmable Controllers: An Engineer's Guide, Third Edition (Programmable Controllers) A. In this study, we propose data mining and data warehousing techniques that could help garner the uneven spread of knowledge and consolidate them together effectively so as to automatically update the self help portals with the top call .. Witten IH, Frank E: Data Mining: Practical Machine Learning Tools and Techniques. Because of the requirement that an epitope be present as a "perfect match" in at least one sequence as described above, 1 and 29 epitopes were removed from the epitope lists for the second and third data sets, respectively. Data mining: Concepts and Techniques.Waltham, MA, USA: Morgan Kaufmann. 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. Data mining: Practical machine learning tools and techniques. Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems). New York: Oxford University Press; 2000. "The third edition of this practical guide to machine learning and data mining is fully updated to account for technological advances since its previous printing in 2005 and is now even more closely aligned with the use of the Weka open source machine learning, data mining and data modeling application. (Morgan Kaufmann Series in Data Management Systems).

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