Anzeige
Erschienen in:
2002 | OriginalPaper | Buchkapitel
XCS and GALE: A Comparative Study of Two Learning Classifier Systems on Data Mining
verfasst von : Ester Bernadó, Xavier Llorà, Josep M. Garrell
Erschienen in: Advances in Learning Classifier Systems
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
This paper compares the learning performance, in terms of prediction accuracy, of two genetic-based learning systems, XCS and GALE, with six well-known learning algorithms, coming from instance based learning, decision tree induction, rule-learning, statistical modeling and support vector machines. The experiments, performed on several datasets, show the suitability of the genetic-based learning classifier systems for classification tasks. Both XCS and GALE significantly achieved better results than IB1 and Naive Bayes. Besides, any method could not outperform XCS and GALE significantly.