Evolving Gaussian mixture models with splitting and merging mutation operators (2016)
- Authors:
- Autor USP: HRUSCHKA, EDUARDO RAUL - ICMC
- Unidade: ICMC
- DOI: 10.1162/EVCO_a_00152
- Subjects: COMPUTAÇÃO EVOLUTIVA; ALGORITMOS GENÉTICOS
- Keywords: Evolutionary algorithms; expectation maximization; Gaussian mixture models; clustering; density estimation
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Evolutionary Computation
- ISSN: 1063-6560
- Volume/Número/Paginação/Ano: v. 24, n. 2, p. 293-317, 2016
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
COVÕES, Thiago Ferreira e HRUSCHKA, Eduardo Raul e GHOSH, Joydeep. Evolving Gaussian mixture models with splitting and merging mutation operators. Evolutionary Computation, v. 24, n. 2, p. 293-317, 2016Tradução . . Disponível em: https://doi.org/10.1162/EVCO_a_00152. Acesso em: 19 set. 2024. -
APA
Covões, T. F., Hruschka, E. R., & Ghosh, J. (2016). Evolving Gaussian mixture models with splitting and merging mutation operators. Evolutionary Computation, 24( 2), 293-317. doi:10.1162/EVCO_a_00152 -
NLM
Covões TF, Hruschka ER, Ghosh J. Evolving Gaussian mixture models with splitting and merging mutation operators [Internet]. Evolutionary Computation. 2016 ; 24( 2): 293-317.[citado 2024 set. 19 ] Available from: https://doi.org/10.1162/EVCO_a_00152 -
Vancouver
Covões TF, Hruschka ER, Ghosh J. Evolving Gaussian mixture models with splitting and merging mutation operators [Internet]. Evolutionary Computation. 2016 ; 24( 2): 293-317.[citado 2024 set. 19 ] Available from: https://doi.org/10.1162/EVCO_a_00152 - An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks
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Informações sobre o DOI: 10.1162/EVCO_a_00152 (Fonte: oaDOI API)
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