Title :
Multiple objective particle swarm for classification-rule discovery
Author :
de Almeida Prado G. Toracio, A. ; Pozo, Aurora T. R.
Author_Institution :
Fed. Univ. of Parana, Curitiba
Abstract :
This paper presents a method of classification-rule discovery based on multiple objective particle swarm technique. The rules are selected at the creation rule process following Pareto dominance concepts and forming unordered classifiers. Initial executions, compared with other algorithms of the literature, show that this approach can be competitive and gives more liberty to choose rules.
Keywords :
Pareto optimisation; data mining; particle swarm optimisation; pattern classification; Pareto dominance; classification-rule discovery; multiple objective particle swarm; Evolutionary computation; Particle swarm optimization;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
DOI :
10.1109/CEC.2007.4424537