rEMM: Extensible Markov Model for Data Stream Clustering in R

rEMM: Extensible Markov Model for Data Stream Clustering in R

Clustering streams of continuously arriving data has become an important application of data mining in recent years and efficient algorithms have been proposed by several researchers. However, clustering alone neglects the fact that data in a data stream is not only characterized by the proximity of...

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Bibliographic Details
Main Authors: Michael Hahsler, Margaret H. Dunham
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2010-10-01
Series:Journal of Statistical Software
Subjects:
data mining
data streams
clustering
Markov chain
Online Access:http://www.jstatsoft.org/v35/i05/paper

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