Genetic Programming for Combining Neural Networks for Drug Discovery

Autor:	Bernard F. Buxton, S. J. Barrett, William B. Langdon
Rok vydání:	2002
Předmět:	Convex hull Artificial neural network Receiver operating characteristic Computer science business.industry Artificial neural network model Genetic programming Artificial intelligence business Classifier (UML)
Zdroj:	Soft Computing and Industry ISBN: 9781447111016
DOI:	10.1007/978-1-4471-0123-9_51
Popis:	We have previously shown [Langdon and Buxton, 2001b] on a range of benchmarks genetic programming (GP) can automatically fuse given classifiers of diverse types to produce a combined classifier whose Receiver Operating Characteristics (ROC) are better than [Scott et al., 1998]’s “Maximum Realisable Receiver Operating Characteristics” (MRROC). i.e. better than their convex hull. Here our technique is used in a blind trial where artificial neural networks are trained by Clementine on P450 pharmaceutical data. Using just the networks, GP automatically evolves a composite classifier.
Databáze:	OpenAIRE
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