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» Improvements to the scalability of multiobjective clustering
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CEC
2005
IEEE
13 years 10 months ago
Improvements to the scalability of multiobjective clustering
In previous work, we have proposed a novel approach to data clustering based on the explicit optimization of a partitioning with respect to two complementary clustering objectives ...
Julia Handl, Joshua D. Knowles
GECCO
2004
Springer
244views Optimization» more  GECCO 2004»
13 years 10 months ago
Using Clustering Techniques to Improve the Performance of a Multi-objective Particle Swarm Optimizer
In this paper, we present an extension of the heuristic called “particle swarm optimization” (PSO) that is able to deal with multiobjective optimization problems. Our approach ...
Gregorio Toscano Pulido, Carlos A. Coello Coello
GECCO
2005
Springer
144views Optimization» more  GECCO 2005»
13 years 10 months ago
Multiobjective hBOA, clustering, and scalability
This paper describes a scalable algorithm for solving multiobjective decomposable problems by combining the hierarchical Bayesian optimization algorithm (hBOA) with the nondominat...
Martin Pelikan, Kumara Sastry, David E. Goldberg
TSE
2011
111views more  TSE 2011»
12 years 12 months ago
Software Module Clustering as a Multi-Objective Search Problem
Software module clustering is the problem of automatically organising software units into modules to improve program structure. There has been a great deal of recent interest in s...
Kata Praditwong, Mark Harman, Xin Yao
GECCO
2006
Springer
144views Optimization» more  GECCO 2006»
13 years 8 months ago
On semi-supervised clustering via multiobjective optimization
Semi-supervised classification uses aspects of both unsupervised and supervised learning to improve upon the performance of traditional classification methods. Semi-supervised clu...
Julia Handl, Joshua D. Knowles