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A Distributed Clustering Algorithm

Hulth, Nils LU and Grenholm, P (1998)
Abstract
A new algorithm for clustering is presented --- the Distributed Clustering Algorithm (DCA). It is designed to be incremental and to work in a real-time situation, thus making it suitable for robotics and in models of concept formation. The DCA starts with one cluster (or rather prototype at the center of the cluster), successively adding prototypes and distributing them according to data density until a certain criteria is fulfilled. This criteria is that new prototypes do not add enough extra precision in the representation of the data. A local measure called emph{roundness} is used to predict how much extra precision a new prototype will add.
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organization
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Working Paper
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published
subject
keywords
Cognitive Studies
language
English
LU publication?
yes
id
9b55bc96-eb29-4b0c-b5ed-490597ac9bd7 (old id 525880)
alternative location
http://www.lucs.lu.se/ftp/pub/LUCS_Studies/LUCS74.pdf
date added to LUP
2007-10-04 16:43:51
date last changed
2016-04-16 12:36:53
@misc{9b55bc96-eb29-4b0c-b5ed-490597ac9bd7,
  abstract     = {A new algorithm for clustering is presented --- the Distributed Clustering Algorithm (DCA). It is designed to be incremental and to work in a real-time situation, thus making it suitable for robotics and in models of concept formation. The DCA starts with one cluster (or rather prototype at the center of the cluster), successively adding prototypes and distributing them according to data density until a certain criteria is fulfilled. This criteria is that new prototypes do not add enough extra precision in the representation of the data. A local measure called emph{roundness} is used to predict how much extra precision a new prototype will add.},
  author       = {Hulth, Nils and Grenholm, P},
  keyword      = {Cognitive Studies},
  language     = {eng},
  title        = {A Distributed Clustering Algorithm},
  year         = {1998},
}