Created by W.Langdon from gp-bibliography.bib Revision:1.4771
Uses correlation coefficient in fitness function as advocated by M. C. South Phd 1994 'The application of GAs to rule finding in data analysis', Newcastle upon Tyne, UK
Final fixup? 'Mutation...replaces a node in the tree with another of the same degree'. Elitist. Pop size 20, G=100, Pcross=0.8 Pmut=0.5 'found to give good performance to date'
'non linear least-squares optimization to obtain 'best' value of the (new) constant(s) in the expression'. 'the fitness of a tree is weighted according to its size' (penalise bigger) Anti-bloat
2nd example 'Near Infra-red reflectance instrument for the inference of the protein contents of ground wheat' (old data, (1983, T.Fearn 'A misuse of ridge regression in the calibration of near infrared reflectance instrument', Appl Statistics, 32, 1, 73-79), various techniques already tried). GP 'provide simple non-linear model that provides far greater insight into the input-output model structure than other non-linear modelling techniques such as neural networks' RMS error also better than cited in literature (traditional stats and ANN).
3rd: recovery of contaminated transformer oil. GP solution robust to measurement error.",
Genetic Programming entries for Ben McKay Mark J Willis Geoffrey W Barton