Title :
Optimising a neural tree classifier using a genetic algorithm
Author :
Pensuwon, Wanida ; Adams, Rod ; Davey, Neil
Author_Institution :
Dept. of Comput. Sci., Hertfordshire Univ., Hatfield, UK
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
Keywords :
genetic algorithms; neural nets; pattern classification; trees (mathematics); clustering measures; dynamic neural tree model; experiments; fitness functions; genetic algorithm; genomic evolution; genotypes; neural tree classifier optimisation; ontogeny; performance; Bioinformatics; Classification tree analysis; Clustering algorithms; Computer science; Counting circuits; Genetic algorithms; Genomics; Mirrors; Tree data structures; Vehicle dynamics;
Conference_Titel :
Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-6400-7
DOI :
10.1109/KES.2000.884179
