Created by W.Langdon from gp-bibliography.bib Revision:1.2031
@InProceedings{langdon:2001:wsc6,
author = "W. B. Langdon and S. J. Barrett and B. F. Buxton",
title = "Genetic Programming for Combining Neural Networks for
Drug Discovery",
booktitle = "Soft Computing and Industry Recent Applications",
year = "2001",
editor = "Rajkumar Roy and Mario K{\"o}ppen and Seppo Ovaska and
Takeshi Furuhashi and Frank Hoffmann",
pages = "597--608",
month = "10--24 " # sep,
publisher = "Springer-Verlag",
note = "Published 2002",
keywords = "genetic algorithms, genetic programming, data fusion,
data mining, knowledge discovery, Receiver Operating
Characteristics, ensemble of classifiers, size fair
crossover",
ISBN = "1-85233-539-4",
URL = "
http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/WBL_wsc6.pdf",
abstract = "We have previously shown on a range of benchmarks
\cite{langdon:2001:gROC} Genetic programming (GP) can
automatically fuse given classifers of diverse types to
produce a combined classifer whose Receiver Operating
Characteristics (ROC) are better than
\cite{scott:1998:BMVC}'s {"}Maximum Realisable Receiver
Operating Characteristics{"} (MRROC). I.e. better than
their convex hull. Here our technique is used in a
blind trial where artifcial neural networks ANN. are
trained by Clementine on P450 pharmaceutical data.
Using just the networks GP automatically evolves a
composite classifer.",
notes = "Out of print?
http://www.amazon.co.uk/Soft-Computing-Industry-Recent-Applications/dp/1852335394
",
}
Genetic Programming entries for William B Langdon S J Barrett Bernard Buxton