Unsupervised learning of Gaussian mixture models: evolutionary create and eliminate for expectation maximization algorithm (2013)
- Authors:
- Autor USP: HRUSCHKA, EDUARDO RAUL - ICMC
- Unidade: ICMC
- DOI: 10.1109/CEC.2013.6557962
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2013
- ISBN: 9781479904549
- Source:
- Título do periódico: Proceedings
- Conference titles: IEEE Congress on Evolutionary Computation - CEC
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
COVÕES, Thiago F e HRUSCHKA, Eduardo Raul. Unsupervised learning of Gaussian mixture models: evolutionary create and eliminate for expectation maximization algorithm. 2013, Anais.. Piscataway: IEEE, 2013. Disponível em: https://doi.org/10.1109/CEC.2013.6557962. Acesso em: 25 abr. 2024. -
APA
Covões, T. F., & Hruschka, E. R. (2013). Unsupervised learning of Gaussian mixture models: evolutionary create and eliminate for expectation maximization algorithm. In Proceedings. Piscataway: IEEE. doi:10.1109/CEC.2013.6557962 -
NLM
Covões TF, Hruschka ER. Unsupervised learning of Gaussian mixture models: evolutionary create and eliminate for expectation maximization algorithm [Internet]. Proceedings. 2013 ;[citado 2024 abr. 25 ] Available from: https://doi.org/10.1109/CEC.2013.6557962 -
Vancouver
Covões TF, Hruschka ER. Unsupervised learning of Gaussian mixture models: evolutionary create and eliminate for expectation maximization algorithm [Internet]. Proceedings. 2013 ;[citado 2024 abr. 25 ] Available from: https://doi.org/10.1109/CEC.2013.6557962 - An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks
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Informações sobre o DOI: 10.1109/CEC.2013.6557962 (Fonte: oaDOI API)
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