Name: Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining (en Inglés)
SKU: 66336787
Price: 172042.00 COP
Availability: InStock
Author: Lopes Veloso, Lays Helena; Senger, Luciano José
ISBN: 9786209114083

portada Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining (en Inglés)

Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining (en Inglés)

Formato

Libro Físico

Editorial

Our Knowledge Publishing

Autor

Lopes Veloso, Lays Helena; Senger, Luciano José

Idioma

Inglés

N° páginas

Encuadernación

Tapa Blanda

Dimensiones

22.9x15.2x0.3 cm

ISBN13

9786209114083

Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining (en Inglés)

Lopes Veloso, Lays Helena; Senger, Luciano José (Autor) · Our Knowledge Publishing · Tapa Blanda

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Reseña del libro "Parallel K-Means Algorithm based on Hadoop-MapReduce for Mining (en Inglés)"

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.