Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining
Language: English
Published by Omniscriptum, Our Knowledge Publishing Okt 2025, 2025
- Softcover
- New
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
AbeBooks seller since January 11, 2012
Condition: New
£ 35.24
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This item is printed on demand - it takes 3-4 days longer - Neuware -This work aimed to investigate the use of a parallel K-Means clustering algorithm, based on the MapReduce programming model, to improve the response time of data mining. The algorithm's performance was evaluated in terms of SpeedUp and ScaleUp. To this end, experiments were performed on a Hadoop cluster consisting of six computers with standard hardware. The clustered data are measurements from flow towers in agricultural regions and belong to Ameriflux. The experiments were performed using 3, 4, and 6 machines, respectively. The results showed that with the increase in the number of machines, there was a gain in performance, with the best time obtained using six machines, reaching a SpeedUp of 3.25. It was found that the application scales well with the equivalent increase in data size and number of machines in the cluster, achieving similar performance in the tests. 56 pp. Englisch.
Seller Inventory # 9786209114083
- Title
- Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining
- Author
- Lays Helena Lopes Veloso
- Publisher
- Omniscriptum, Our Knowledge Publishing Okt 2025
- Publication year
- 2025
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 6209114083
- ISBN 13
- 9786209114083
- Dimensions
- 220x150x33 mm
"Synopsis" may belong to another edition of this title.
BuchWeltWeit Ludwig Meier e.K.
Bergisch Gladbach, Germany
AbeBooks seller since January 11, 2012
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