Bi-objective evolutionary hyper-heuristics in automated machine learning for text classification tasks

This paper proposes an evolutionary model based on hyper-heuristics to automate the selection of classification methods for text datasets under a bi-objective approach. The model has three nested levels. At the first level, individual methods classify datasets, recording two performances: the number...

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Vydané v:	Swarm and evolutionary computation Ročník 98; s. 102073
Hlavní autori:	Estrella-Ramírez, Jonathan, de la Calleja, Jorge, Carranza, Juan Carlos Gómez
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 01.10.2025
Predmet:	Automated machine learning Genetic algorithms Hyper-heuristics Multi-objective optimization Text classification Automated machine learning Multi-objective optimization Hyper-heuristics Text classification Genetic algorithms
ISSN:	2210-6502
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