Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression

Research article (Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022) · cited 15× · AI/ML
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Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression

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Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression. Retrieved May 24, 2026, from https://4ort.xyz/entity/bayesian-model-selection-for-reducing-bloat-and-overfitting-in-genetic-programming-for-symbolic-regression
MLA “Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/bayesian-model-selection-for-reducing-bloat-and-overfitting-in-genetic-programming-for-symbolic-regression.
BibTeX @misc{4ortxyz_bayesian-model-selection-for-reducing-bloat-and-overfitting-in-genetic-programming-for-symbolic-regression_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Bayesian model selection for reducing bloat and overfitting in genetic programming for symbolic regression}}, year = {2026}, url = {https://4ort.xyz/entity/bayesian-model-selection-for-reducing-bloat-and-overfitting-in-genetic-programming-for-symbolic-regression}, note = {Accessed: 2026-05-24}}
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