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Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations (The Morgan Kaufmann Series in Data Management Systems) Paperback – 20 Oct 1999

4.3 out of 5 stars 4 customer reviews

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Product details

  • Paperback: 371 pages
  • Publisher: Morgan Kaufmann (20 Oct. 1999)
  • Language: English
  • ISBN-10: 1558605525
  • ISBN-13: 978-1558605527
  • Product Dimensions: 23.2 x 18.5 x 2.1 cm
  • Average Customer Review: 4.2 out of 5 stars 4 customer reviews
  • Amazon Bestsellers Rank: 1,290,548 in Books (See Top 100 in Books)
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Product description

Review

"This is a milestone in the synthesis of data mining, data analysis, information theory, and machine learning."
—Jim Gray, Microsoft 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.

Eibe Frank lives in New Zealand with his Samoan spouse and two lovely boys, but originally hails from Germany, where he received his first degree in computer science from the University of Karlsruhe. He moved to New Zealand to pursue his Ph.D. in machine learning under the supervision of Ian H. Witten, and joined the Department of Computer Science at the University of Waikato as a lecturer on completion of his studies. He is now an associate professor at the same institution. As an early adopter of the Java programming language, he laid the groundwork for the Weka software described in this book. He has contributed a number of publications on machine learning and data mining to the literature and has refereed for many conferences and journals in these areas.>


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Most helpful customer reviews on Amazon.com

Amazon.com: 3.4 out of 5 stars 15 reviews
35 people found this helpful.
5.0 out of 5 starsExcellent introduction to data mining algorithms
on 7 February 2000 - Published on Amazon.com
Format: Paperback
13 people found this helpful.
5.0 out of 5 starsData mining technology power on 400 pages.
on 28 February 2002 - Published on Amazon.com
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4 people found this helpful.
5.0 out of 5 starsA nice complement to the other data mining bible
on 8 July 2005 - Published on Amazon.com
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9 people found this helpful.
5.0 out of 5 starsStop searching for datamining: You've found it.
on 5 April 2004 - Published on Amazon.com
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15 people found this helpful.
5.0 out of 5 starsOur most popular book
on 16 August 2001 - Published on Amazon.com
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