A Distributed Clustering Algorithm

Forskningsoutput: Working paper

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.

Detaljer

Författare
  • Nils Hulth
  • P Grenholm
Enheter & grupper
Forskningsområden

Ämnesklassifikation (UKÄ) – OBLIGATORISK

  • Filosofi

Nyckelord

Originalspråkengelska
StatusPublished - 1998
PublikationskategoriForskning