Title :
Dynamic clustering of interval data based on adaptive Chebyshev distances
Author :
de Souza, R.M.C.R. ; de Carvalho, F.A.T.
Author_Institution :
Comput. Sci. Center, Fed. Univ. of Pernambuco, Recife, Brazil
fDate :
5/27/2004 12:00:00 AM
Abstract :
A dynamic clustering method for interval data is presented. This method furnishes a partition and a prototype for each cluster by optimising a criterion based on adaptive Chebyshev distances. Experiments with real and artificial interval data sets have demonstrated the usefulness of this method.
Keywords :
Chebyshev approximation; data analysis; pattern clustering; statistical analysis; adaptive Chebyshev distances; artificial interval data sets; dynamic clustering method; optimisation; prototypes; real interval data sets;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20040440
