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MCS
2001
Springer
13 years 9 months ago
Genetic Programming for Improved Receiver Operating Characteristics
Genetic programming (GP) can automatically fuse given classifiers of diverse types to produce a combined classifier whose Receiver Operating Characteristics (ROC) are better than...
William B. Langdon, Bernard F. Buxton
EVOW
2003
Springer
13 years 10 months ago
Comparison of AdaBoost and Genetic Programming for Combining Neural Networks for Drug Discovery
Genetic programming (GP) based data fusion and AdaBoost can both improve in vitro prediction of Cytochrome P450 activity by combining artificial neural networks (ANN). Pharmaceuti...
William B. Langdon, S. J. Barrett, Bernard F. Buxt...
GECCO
2006
Springer
218views Optimization» more  GECCO 2006»
13 years 8 months ago
A survey of mutation techniques in genetic programming
The importance of mutation varies across evolutionary computation domains including: genetic programming, evolution strategies, and genetic algorithms. In the genetic programming ...
Alan Piszcz, Terence Soule
EUROGP
2007
Springer
135views Optimization» more  EUROGP 2007»
13 years 11 months ago
A Grammatical Genetic Programming Approach to Modularity in Genetic Algorithms
The ability of Genetic Programming to scale to problems of increasing difficulty operates on the premise that it is possible to capture regularities that exist in a problem environ...
Erik Hemberg, Conor Gilligan, Michael O'Neill, Ant...
CEC
2009
IEEE
13 years 11 months ago
Implicit Context Representation Cartesian Genetic Programming for the assessment of visuo-spatial ability
— In this paper, a revised form of Implicit Context Representation Cartesian Genetic Programming is used in the development of a diagnostic tool for the assessment of patients wi...
Stephen L. Smith, Michael A. Lones