A Hybrid Genetic Programming Neural Network Classifier for Use in Drug Discovery

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{his02Plenary:Langdon,
  pages =        "6",
  year =         "2002",
  title =        "A Hybrid Genetic Programming Neural Network Classifier
                 for Use in Drug Discovery",
  editor =       "Ajith Abraham and Javier {Ruiz-del-Solar} and 
                 Mario K{\"o}ppen",
  chapter =      "Abstracts of HIS02 Plenary Presentations",
  series =       "Frontiers in Artificial Intelligence and Applications
                 Vol. 87",
  institution =  "Department of Computer Science -- University College
                 London -- UK",
  booktitle =    "Soft Computing Systems - Design, Management and
                 Applications",
  publisher =    "IOS Press Amsterdam, Berlin, Oxford, Tokyo, Washington
                 D.C.",
  author =       "William B. Langdon",
  month =        "1-4 " # dec,
  abstract =     "We have shown genetic programming (GP) can
                 automatically fuse given classifiers of diverse types
                 to produce a hybrid classifier. Combinations of neural
                 networks, decision trees and Bayes classifier shave
                 been formed. On a range of benchmarks the evolved
                 multiple classifier system is better than all of its
                 components. Indeed its Receiver Operating
                 Characteristics (ROC) are better than [Scott et al.,
                 1998]s {"}Maximum Realisable Receiver Operating
                 Characteristics{"} MRROC (convex hull) An important
                 component in the drug discovery is testing potential
                 drugs for activity with P450 cell membrane molecules.
                 Our technique has been used in a blind trial where
                 artificial neural networks are trained by Clementine on
                 P450 pharmaceutical data. Using just the trained
                 networks, GP automatically evolves a composite
                 classifier. Recent experiments with boosting the
                 networks will be compared with genetic programming.",
  note =         "Invited conference speaker",
  address =      "Universidad de Chile, Chile",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-58603-297-6",
  URL =          "http://www.cec.uchile.cl/~his02/index_files/abs_drug.pdf",
  size =         "1 page",
  notes =        "http://www.cec.uchile.cl/~his02/index.html old key
                 langdon:2002:his

                 ISBN? = 4 274 90558 6 C3055",
}

Genetic Programming entries for William B Langdon

Citations