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Data Mining: Know It All

Data Mining: Know It All
Authors
Soumen Chakrabarti, Earl Cox, Eibe Frank, Ralf Hartmut Gting, Jiawei Han, Xia Jiang, Micheline Kamber, Sam S. Lightstone, Thomas P. Nadeau, Richard E Neapolitan, Dorian Pyle, Mamdouh Refaat, Markus Schneider, Toby J. Teorey, Ian H. Witten
ISBN
0123746299
Published
21 Nov 2008
Purchase online
amazon.com

This book brings all of the elements of data mining together in a single volume, saving the reader the time and expense of making multiple purchases. It consolidates both introductory and advanced topics, thereby covering the gamut of data mining and machine learning tactics ? from data integration and pre-processing, to fundamental algorithms, to optimization techniques and web mining methodology.

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  1. Editorial Reviews
  2. Customer Reviews

Customer Reviews

R. Starr said
Part of the value of a book like this is to get relevant, well-focused pointers into the larger literature. Some chapters have "resources" sections; some "resources" sections have bibliographies. There is no consistent pattern to the coverage. Finally, and most damaging, many resources are simply missing: "Hartigan, 1975" is all you'll get to find out more about variations of k-means clustering.

I hope the publisher will rectify this by providing adequate bibliographical materials on their website or in later editions.

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