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• W2598506151 abstract "This chapter proposes a generic framework to build geometric dispersion (GD) operators for Geometric Semantic Genetic Programming in the context of symbolic regression, followed by two concrete instantiations of the framework: a multiplicative geometric dispersion operator and an additive geometric dispersion operator. These operators move individuals in the semantic space in order to balance the population around the target output in each dimension, with the objective of expanding the convex hull defined by the population to include the desired output vector. An experimental analysis was conducted in a testbed composed of sixteen datasets showing that dispersion operators can improve GSGP search and that the multiplicative version of the operator is overall better than the additive version." @default.
• W2598506151 created "2017-04-07" @default.
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• W2598506151 date "2018-01-01" @default.
• W2598506151 modified "2023-09-23" @default.
• W2598506151 title "A Generic Framework for Building Dispersion Operators in the Semantic Space" @default.
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• W2598506151 doi "https://doi.org/10.1007/978-3-319-97088-2_12" @default.
• W2598506151 hasPublicationYear "2018" @default.
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