A connectionist machine for genetic hillclimbing
A connectionist machine for genetic hillclimbing
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Learning Bayesian networks with local structure
Learning in graphical models
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
Proceedings of the 5th International Conference on Genetic Algorithms
A comparison of selection schemes used in evolutionary algorithms
Evolutionary Computation
Combinatorial effects of local structures and scoring metrics in bayesian optimization algorithm
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Intelligent bias of network structures in the hierarchical BOA
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Mining probabilistic models learned by EDAs in the optimization of multi-objective problems
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Analyzing probabilistic models in hierarchical BOA
IEEE Transactions on Evolutionary Computation - Special issue on evolutionary algorithms based on probabilistic models
Spurious dependencies and EDA scalability
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Empirically studying the role of selection operators duringsearch-based test suite prioritization
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Sensibility of linkage information and effectiveness of estimated distributions
Evolutionary Computation
Hi-index | 0.00 |
This paper addresses selection as a source of overfitting in Bayesian estimation of distribution algorithms (EDAs). The purpose of the paper is twofold. First, it shows how the selection operator can lead to model overfitting in the Bayesian optimization algorithm (BOA). Second, the metric score that guides the search for an adequate model structure is modified to take into account the non-uniform distribution of the mating pool generated by tournament selection.