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Data mining: practical machine learning tools and techniques / Ian H. Witten, Eibe Frank, Mark A. Hall.

By: Witten, Ian H.
Contributor(s): Hall, Mark A.
Material type: materialTypeLabelBookSeries: Publisher: Burlington, MA : Morgan Kaufmann/ Elsevier, [2011]Copyright date: ©2011Edition: 3rd edition.Description: xxxiii, 629 pages : ills. ; 24cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780123748560 (pbk).Subject(s): Data miningSummary: Summary: As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is n o magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data.
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Item type Current location Call number Status Date due Barcode Item holds
Books Books Graduate School Library
GRAD QA 76.9 D343W58 2011 (Browse shelf) Available 2015-23536-01-1
Books Books PUP Commonwealth Library
QA 76.9 D343W58 2011 (Browse shelf) Available 2014-23416-01-1
Total holds: 0

Summary: As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is n o magic in machine learning, no hidden power, no alchemy. Instead there is an identifiable body of practical techniques that can extract useful information from raw data.

C&E Publishing, Purchased 8-1-2014 2014-23416-01-1 3,148.00

GBSI Purchased 2-4-2015 2015-23536-01-1 6,650.00

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