Soft computing deals with evolutionary and fuzzy computation. Here are the
instructions to visit an on-line conference, perhaps a model of what Unrev
folks should be doing.
Jack
<note>resent because I forgot to install a subject line</note>
>To: genetic-programming@cs.stanford.edu
>Date: Mon, 10 Sep 2001 10:23:40 +0100
>From: Bill LANGDON <W.Langdon@cs.ucl.ac.uk>
>Sender: owner-genetic-programming@lists.Stanford.EDU
>Reply-To: Bill LANGDON <W.Langdon@cs.ucl.ac.uk>
>
>Subject:WSC6 paper "Genetic Programming for Combining Neural Networks for
>Drug Discovery"
>--------
>We have a paper on using GP to combine ANN classifiers and
>demonstrating it on a Bioinformatics (P450 activity prdiction) problem.
>
>This is being presented now at the
>6th Online World Conference on Soft Computing
>
>
>Steps:
>
>0. go to http://www.vision.fhg.de/wsc6/
>1. Register (its free)
>2. Enter Conference
>3. Sessions
>4. New Evolutionary Algorithms
>5. Paper019
>
>Paper No. 019:
> Genetic Programming for Combining Neural
> Networks for Drug Discovery
> W. B. Langdon, S. J. Barrett, B. F. Buxton
> (paper) (presentation)
> Abstract
> We have previously shown on a range of benchmarks
> [Langdon,2001] Genetic programming (GP) can
> automatically fuse given classifers of diverse types to
> produce a combined classifer whose Receiver
> Operating Characteristics (ROC) are better than
> [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. are trained by
> Clementine on P450 pharmaceutical data. Using just the
> networks GP automatically evolves a composite
> classifer.
>
>6. Checkout "presentation" (eg movie)
>
>7. "post" comments
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