Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Robust Classification for Imprecise Environments
Machine Learning
Machine Learning
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Evolving Receiver Operating Characteristics for Data Fusion
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Adaptive mixtures of local experts
Neural Computation
Combining Multiple Experts for Classifying Shot Changes in Video Sequences
ICMCS '99 Proceedings of the 1999 IEEE International Conference on Multimedia Computing and Systems - Volume 02
Combining Decision Trees and Neural Networks for Drug Discovery
EuroGP '02 Proceedings of the 5th European Conference on Genetic Programming
The use of artificial-intelligence-based ensembles for intrusion detection: a review
Applied Computational Intelligence and Soft Computing
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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.1998b]'s "Maximum Realisable Receiver Operating Characteristics" (MRROC). I.e. better than their convex hull. This is demonstrated on a satellite image processing bench mark using Naive Bayes, Decision Trees (C4.5) and Clementine artificial neural networks.