Abstract
Statistical techniques for designing and analyzing experiments are used to evaluate the individual and combined effects of genetic programming parameters. Three binary classification problems are investigated in a total of seven experiments consisting of 1108 runs of a machine code genetic programming system. The parameters having the largest effect in these experiments are the population size and the number of generations. A large number of parameters have negligible effects. The experiments indicate that the investigated genetic programming system is robust to parameter variations, with the exception of a few important parameters.
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© 2000 Springer-Verlag Berlin Heidelberg
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Feldt, R., Nordin, P. (2000). Using Factorial Experiments to Evaluate the Effect of Genetic Programming Parameters. In: Poli, R., Banzhaf, W., Langdon, W.B., Miller, J., Nordin, P., Fogarty, T.C. (eds) Genetic Programming. EuroGP 2000. Lecture Notes in Computer Science, vol 1802. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-46239-2_20
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DOI: https://doi.org/10.1007/978-3-540-46239-2_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-67339-2
Online ISBN: 978-3-540-46239-2
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