A study of K-means-based algorithms for constrained clustering (2013)
- Authors:
- Autor USP: HRUSCHKA, EDUARDO RAUL - ICMC
- Unidade: ICMC
- DOI: 10.3233/IDA-130590
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Intelligent Data Analysis
- ISSN: 1088-467X
- Volume/Número/Paginação/Ano: v. 17, n. 3, p. 485-505, 2013
- 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. A study of K-means-based algorithms for constrained clustering. Intelligent Data Analysis, v. 17, n. 3, p. 485-505, 2013Tradução . . Disponível em: https://doi.org/10.3233/IDA-130590. Acesso em: 23 abr. 2024. -
APA
Covões, T. F., Hruschka, E. R., & Ghosh, J. (2013). A study of K-means-based algorithms for constrained clustering. Intelligent Data Analysis, 17( 3), 485-505. doi:10.3233/IDA-130590 -
NLM
Covões TF, Hruschka ER, Ghosh J. A study of K-means-based algorithms for constrained clustering [Internet]. Intelligent Data Analysis. 2013 ; 17( 3): 485-505.[citado 2024 abr. 23 ] Available from: https://doi.org/10.3233/IDA-130590 -
Vancouver
Covões TF, Hruschka ER, Ghosh J. A study of K-means-based algorithms for constrained clustering [Internet]. Intelligent Data Analysis. 2013 ; 17( 3): 485-505.[citado 2024 abr. 23 ] Available from: https://doi.org/10.3233/IDA-130590 - An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks
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Informações sobre o DOI: 10.3233/IDA-130590 (Fonte: oaDOI API)
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