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View all- Sambo AAzad RKovalchuk YIndramohan VShah H(2021)Evolving simple and accurate symbolic regression models via asynchronous parallel computingApplied Soft Computing10.1016/j.asoc.2021.107198104:COnline publication date: 1-Jun-2021
In genetic programming (GP), controlling complexity often means reducing the size of evolved expressions. However, previous studies show that size reduction may not avoid model overfitting. Therefore, in this study, we use the evaluation time --- the ...
In machine learning, reducing the complexity of a model can help to improve its computational efficiency and avoid overfitting. In genetic programming (GP), the model complexity reduction is often achieved by reducing the size of ...
Genetic Programming (GP) homologous crossovers are a group of operators, including GP one-point crossover and GP uniform crossover, where the offspring are created preserving the position of the genetic material taken from the parents. In this paper we ...
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