About: A Generic Framework for Building Dispersion Operators in the Semantic Space

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type	http://eprints.org/ontology/BookSectionEPrint http://eprints.org/ontology/EPrint Article Book Section
seeAlso	HTML Summary of #59297 A Generic Framework for Building Dispersion Operators in the Semantic Space
sameAs	A Generic Framework for Building Dispersion Operators in the Semantic Space
http://eprints.org/ontology/hasAccepted	A Generic Framework for Building Dispersion Operators in the Semantic Space (PDF)
http://eprints.org/ontology/hasDocument	A Generic Framework for Building Dispersion Operators in the Semantic Space (Other) A Generic Framework for Building Dispersion Operators in the Semantic Space (Other) A Generic Framework for Building Dispersion Operators in the Semantic Space (Other) A Generic Framework for Building Dispersion Operators in the Semantic Space (Other) A Generic Framework for Building Dispersion Operators in the Semantic Space (PDF) A Generic Framework for Building Dispersion Operators in the Semantic Space (Other)
dc:hasVersion	A Generic Framework for Building Dispersion Operators in the Semantic Space (PDF)
Title	A Generic Framework for Building Dispersion Operators in the Semantic Space
described by	https://demo.openlinksw.com/about/id/entity/https/www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2018-11-08
Creator	Fernando E.B. Otero Gisele L. Pappa Luiz O.V.B. Oliveira
status	peer reviewed published
Publisher	Springer
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.
Is Part Of	https://kar.kent.ac.uk/id/repository
Subject	Q335 Artificial intelligence
list of authors	https://kar.kent.ac.uk/id/eprint/59297#authors
is topic of	https://www.cs.kent.ac.uk/people/staff/akj22/materials/CO644/export_kar_RDFN3.n3 https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #59297 A Generic Framework for Building Dispersion Operators in the Semantic Space

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