Multiple criteria genetic algorithms for feature selection in neurofuzzy modelling

Emmanoulidis, C. and Hunter, Andrew and MacIntyre, J. and Cox, C. (1999) Multiple criteria genetic algorithms for feature selection in neurofuzzy modelling. In: International Joint Conference on Neural Networks, 12-17 July 1999, Washington DC.

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Full text URL: http://dx.doi.org/10.1109/IJCNN.1999.830875

Abstract

This paper discusses the use of multicriteria genetic algorithms for feature selection in classification problems. This feature selection approach is shown to yield a diverse population of alternative feature subsets with various accuracy/complexity trade-off. The algorithm is applied to select features for performing classification with fuzzy models, and is evaluated on two real-world data sets. We discuss when multicriteria genetic algorithm feature selection is preferable to a sequential feature selection procedure, namely backwards elimination. Among the key features of the presented approach are its computational simplicity, effectiveness on real world problems and the potential it has to become a powerful tool aiding many empirical modeling and data mining processes

Item Type:Conference or Workshop Item (Paper)
Additional Information:This paper discusses the use of multicriteria genetic algorithms for feature selection in classification problems. This feature selection approach is shown to yield a diverse population of alternative feature subsets with various accuracy/complexity trade-off. The algorithm is applied to select features for performing classification with fuzzy models, and is evaluated on two real-world data sets. We discuss when multicriteria genetic algorithm feature selection is preferable to a sequential feature selection procedure, namely backwards elimination. Among the key features of the presented approach are its computational simplicity, effectiveness on real world problems and the potential it has to become a powerful tool aiding many empirical modeling and data mining processes
Keywords:neurofuzzy, genetic algorithm, multiple criteria
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
Divisions:College of Science > School of Computer Science
ID Code:2832
Deposited By: Rosaline Smith
Deposited On:09 Jul 2010 08:21
Last Modified:18 Jul 2011 16:27

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