REMOLD: An Efficient Model-Based Clustering Algorithm for Large Datasets with Spark

Density-based clustering algorithms have the distinctive advantage of discovering arbitrarily shaped clusters, but they usually require a procedure to compute the distance between every pair of data points, and this procedure is prohibitive for large datasets since it has quadratic computation compl...

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Bibliographic Details

Published in:	2017 IEEE 23rd International Conference on Parallel and Distributed Systems (ICPADS) pp. 376 - 383
Main Authors:	Liang, Mingfei, Li, Qingyong, Geng, Yangli-ao, Wang, Jianzhu, Wei, Zhi
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2017
Subjects:	Clustering algorithms Computational modeling density estimation density-based clustering distributed clustering Estimation Gaussian model Kernel Load modeling Partitioning algorithms Spark Sparks
ISSN:	1521-9097
Online Access:	Get full text
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