On the efficiency of evolutionary fuzzy clustering

Campello, Ricardo J.G.B., Hruschka, Eduardo R., and Alves, Vinícius S. (2009) On the efficiency of evolutionary fuzzy clustering. Journal of Heuristics, 15 (1). pp. 43-75.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website: http://dx.doi.org/10.1007/s10732-007-905...
 
31
2


Abstract

This paper tackles the problem of showing that evolutionary algorithms for fuzzy clustering can be more efficient than systematic (i.e. repetitive) approaches when the number of clusters in a data set is unknown. To do so, a fuzzy version of an Evolutionary Algorithm for Clustering (EAC) is introduced. A fuzzy cluster validity criterion and a fuzzy local search algorithm are used instead of their hard counterparts employed by EAC. Theoretical complexity analyses for both the systematic and evolutionary algorithms under interest are provided. Examples with computational experiments and statistical analyses are also presented.

Item ID: 47655
Item Type: Article (Research - C1)
ISSN: 1572-9397
Keywords: complexity analyses; evolutionary algorithms; fuzzy clustering; performance comparison
Date Deposited: 13 Mar 2017 01:42
FoR Codes: 01 MATHEMATICAL SCIENCES > 0104 Statistics > 010401 Applied Statistics @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970101 Expanding Knowledge in the Mathematical Sciences @ 100%
Downloads: Total: 2
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page