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The Top Ten Algorithms in Data Mining
By Xindong Wu (editor) and Vipin Kumar (editor)
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Bibliographic Detail
Publisher Chapman & Hall
Publication date April 3, 2009
Pages 215
Binding Hardcover
Book category Adult Non-Fiction
ISBN-13 9781420089646
ISBN-10 1420089641
Dimensions 0.50 by 6.25 by 9.50 in.
Original list price $99.95
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Summaries and Reviews
Amazon.com description: Product Description:

Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research. Thoroughly evaluated by independent reviewers, each chapter focuses on a particular algorithm and is written by either the original authors of the algorithm or world-class researchers who have extensively studied the respective algorithm.

The book concentrates on the following important algorithms: C4.5, k-Means, SVM, Apriori, EM, PageRank, AdaBoost, kNN, Naive Bayes, and CART. Examples illustrate how each algorithm works and highlight its overall performance in a real-world application. The text covers key topics―including classification, clustering, statistical learning, association analysis, and link mining―in data mining research and development as well as in data mining, machine learning, and artificial intelligence courses.

By naming the leading algorithms in this field, this book encourages the use of data mining techniques in a broader realm of real-world applications. It should inspire more data mining researchers to further explore the impact and novel research issues of these algorithms.



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Hardcover
Book cover for 9781420089646
 
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With Xindong Wu (other contributor) | from Chapman & Hall (April 3, 2009)
9781420089646 | details & prices | 215 pages | 6.25 × 9.50 × 0.50 in. | 0.95 lbs | List price $99.95
About: Identifying some of the most influential algorithms that are widely used in the data mining community, The Top Ten Algorithms in Data Mining provides a description of each algorithm, discusses its impact, and reviews current and future research.

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