Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining

Language: English

Published by Our Knowledge Publishing Okt 2025, 2025

6209114083 / 9786209114083

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This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.

Seller Inventory # 9786209114083

Title
Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining
Author
Lays Helena Lopes Veloso
Publisher
Our Knowledge Publishing Okt 2025
Publication year
2025
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6209114083
ISBN 13
9786209114083
Item weight
102 grams
Dimensions
220x150x4 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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