The Top Ten Algorithms in Data Mining
Language: English
Published by CRC Press, 2009
Series: Book 9 of 56 - Chapman & Hall/CRC Data Mining and Knowledge Discovery
- Hardcover
- Used
Seller: Anybook.com, Lincoln, United KingdomAnybook.com
AbeBooks seller since December 22, 1999
Condition: Used - Good
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This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,500grams, ISBN:9781420089646.
Seller Inventory # 5556434
- Title
- The Top Ten Algorithms in Data Mining
- Author
- Wu, X.
- Publisher
- CRC Press
- Publication year
- 2009
- Condition
- Good
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 1420089641
- ISBN 13
- 9781420089646
- Item weight
- 500 grams
- Series
- Book 9 of 56: Chapman & Hall/CRC Data Mining and Knowledge Discovery
- Seller catalogs
- Science & Technology
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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Anybook.com
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