Machine Learning
The evolution of size and shape
Advances in genetic programming
Robust Classification for Imprecise Environments
Machine Learning
Feature-Level and Decision-Level Fusion of Noncoincidently Sampled Sensors for Land Mine Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Genetic Programming and Data Structures: Genetic Programming + Data Structures = Automatic Programming!
Size Fair and Homologous Tree Crossovers for Tree Genetic Programming
Genetic Programming and Evolvable Machines
Too Much Knowledge Hurts: Acceleration of Genetic Programs for Learning Heuristics
Proceedings of the International Conference, 7th Fuzzy Days on Computational Intelligence, Theory and Applications
Evolving Receiver Operating Characteristics for Data Fusion
EuroGP '01 Proceedings of the 4th European Conference on Genetic Programming
Genetic Programming for Improved Receiver Operating Characteristics
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Genetic Algorithms for Multi-classifier System Configuration: A Case Study in Character Recognition
MCS '01 Proceedings of the Second International Workshop on Multiple Classifier Systems
Adaptive mixtures of local experts
Neural Computation
Combination of support vector machines using genetic programming
International Journal of Hybrid Intelligent Systems
Computational Statistics & Data Analysis
Machine learning and genetic algorithms in pharmaceutical development and manufacturing processes
Decision Support Systems
The diversity/accuracy dilemma: an empirical analysis in the context of heterogeneous ensembles
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Feature selection in heterogeneous structure of ensembles: a genetic algorithm approach
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Artificial Intelligence Review
Comparison of adaboost and genetic programming for combining neural networks for drug discovery
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Creating ensembles of classifiers via fuzzy clustering and deflection
Fuzzy Sets and Systems
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Learning regression ensembles with genetic programming at scale
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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Genetic programming (GP) offers a generic method of automatically fusing together classifiers using their receiver operating characteristics (ROC) to yield superior ensembles. We combine decision trees (C4.5) and artificial neural networks (ANN) on a difficult pharmaceutical data mining (KDD) drug discovery application. Specifically predicting inhibition of a P450 enzyme. Training data came from high throughput screening (HTS) runs. The evolved model may be used to predict behaviour of virtual (i.e. yet to be manufactured) chemicals. Measures to reduce over fitting are also described.