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JASIS
2000
143views more  JASIS 2000»
13 years 7 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
CEC
2008
IEEE
13 years 10 months ago
Subtree deactivation control with grammatical Genetic Programming in dynamic environments
Abstract-- We investigate the usefulness of a subtree deactivation control mechanism which is open to evolutionary learning. It is hypothesised that this representation confers an ...
Michael O'Neill, Anthony Brabazon, Erik Hemberg
CORR
2006
Springer
153views Education» more  CORR 2006»
13 years 8 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
ML
2006
ACM
143views Machine Learning» more  ML 2006»
13 years 8 months ago
Mathematical applications of inductive logic programming
The application of Inductive Logic Programming to scientific datasets has been highly successful. Such applications have led to breakthroughs in the domain of interest and have dri...
Simon Colton, Stephen Muggleton
GECCO
2008
Springer
141views Optimization» more  GECCO 2008»
13 years 9 months ago
Managing team-based problem solving with symbiotic bid-based genetic programming
Bid-based Genetic Programming (GP) provides an elegant mechanism for facilitating cooperative problem decomposition without an a priori specification of the number of team member...
Peter Lichodzijewski, Malcolm I. Heywood