CPSCLASS: A constructive particle swarm classifier
Tipo
Artigo
Data de publicação
2012
Periódico
International Journal of Computational Intelligence and Applications
Citações (Scopus)
1
Autores
Szabo A.
De Castro L.N.
De Castro L.N.
Orientador
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Resumo
The data classification task is one of the main tasks within the knowledge discovering from databases field. Its goal is to allow the correct classification of new objects (records from a database), unknown to the classifier, based upon the extraction of knowledge from objects whose classes are known a priori. The known data can be used to generate a classification model, or simply to infer the class of new objects from those whose classes are known. This paper presents a proposal for a classification algorithm, called Constructive Particle Swarm Classifier (cPSClass), which uses mechanisms from the Particles Swarm Clustering algorithm and Artificial Immune Systems to determine dynamically the number of prototypes from a database and use them to predict the correct class to which a new input object should belong. For performance evaluation the cPSClass was applied to several datasets from the literature and its performance was compared with that of its predecessor version, the nonconstructive Particle Swarm Classifier, and also to some classic algorithms from the literature. © 2012 Imperial College Press.
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Assuntos Scopus
Artificial Immune System , Classic algorithm , Classification algorithm , Classification models , Data classification , Data sets , Main tasks , Particle swarm , Performance evaluation