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A Method for Handling Numerical Attributes in GA-Based Inductive Concept Learners
Federico Divina, Maarten Keijzer, and Elena Marchiori
Department of Computer Science
Vrije Universiteit
De Boelelaan 1081a,
1081 HV Amsterdam
The Netherlands
{divina,mkeijzer,elena}@cs.vu.nl
Abstract. This paper proposes a method for dealing with numerical attributes in inductive concept learning systems based on genetic algorithms. The method uses constraints for restricting the range of values of the attributes and novel stochastic operators for modifying the constraints. These operators exploit information on the distribution of the values of an attribute. The method is embedded into a GA based system for inductive logic programming. Results of experiments on various data sets indicate that the method provides an effective local discretization tool for GA based inductive concept learners.
LNCS 2723, p. 898 ff.
lncs@springer.de
© Springer-Verlag Berlin Heidelberg 2003