An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks (2013)
- Authors:
- Autor USP: HRUSCHKA, EDUARDO RAUL - ICMC
- Unidade: ICMC
- DOI: 10.1016/j.datak.2012.12.006
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Source:
- Título: Data & Knowledge Engineering
- ISSN: 0169-023X
- Volume/Número/Paginação/Ano: v. 84, p. 47-58, mar. 2013
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
SILVA, Jonathan de Andrade e HRUSCHKA, Eduardo Raul. An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks. Data & Knowledge Engineering, v. 84, p. 47-58, 2013Tradução . . Disponível em: https://doi.org/10.1016/j.datak.2012.12.006. Acesso em: 28 dez. 2025. -
APA
Silva, J. de A., & Hruschka, E. R. (2013). An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks. Data & Knowledge Engineering, 84, 47-58. doi:10.1016/j.datak.2012.12.006 -
NLM
Silva J de A, Hruschka ER. An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks [Internet]. Data & Knowledge Engineering. 2013 ; 84 47-58.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.datak.2012.12.006 -
Vancouver
Silva J de A, Hruschka ER. An experimental study on the use of nearest neighbor-based imputation algorithms for classification tasks [Internet]. Data & Knowledge Engineering. 2013 ; 84 47-58.[citado 2025 dez. 28 ] Available from: https://doi.org/10.1016/j.datak.2012.12.006 - Unsupervised learning of Gaussian mixture models: evolutionary create and eliminate for expectation maximization algorithm
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Informações sobre o DOI: 10.1016/j.datak.2012.12.006 (Fonte: oaDOI API)
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