Optimising a neural tree classifier using a genetic algorithm
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Author
Pensuwon, W.
Adams, R.G.
Davey, N.
Attention
2299/6718
Abstract
This paper documents experiments performed using a GA to optimise the parameters of a dynamic neural tree model. Two fitness functions were created from two selected clustering measures, and a population of genotypes, specifying parameters of the model were evolved. This process mirrors genomic evolution and ontogeny. It is shown that the evolved parameter values improved performance