Extending k-means-based algorithms for evolving data streams with variable number of clusters (2011)
- Authors:
- Autor USP: HRUSCHKA, EDUARDO RAUL - ICMC
- Unidade: ICMC
- DOI: 10.1109/ICMLA.2011.67
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: IEEE Computer Society
- Publisher place: Los Alamitos
- Date published: 2011
- Source:
- Título: Proceedings
- Conference titles: International Conference on Machine Learning and Applications - ICMLA
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SILVA, Jonathan de Andrade e HRUSCHKA, Eduardo Raul. Extending k-means-based algorithms for evolving data streams with variable number of clusters. 2011, Anais.. Los Alamitos: IEEE Computer Society, 2011. Disponível em: https://doi.org/10.1109/ICMLA.2011.67. Acesso em: 20 jan. 2026. -
APA
Silva, J. de A., & Hruschka, E. R. (2011). Extending k-means-based algorithms for evolving data streams with variable number of clusters. In Proceedings. Los Alamitos: IEEE Computer Society. doi:10.1109/ICMLA.2011.67 -
NLM
Silva J de A, Hruschka ER. Extending k-means-based algorithms for evolving data streams with variable number of clusters [Internet]. Proceedings. 2011 ;[citado 2026 jan. 20 ] Available from: https://doi.org/10.1109/ICMLA.2011.67 -
Vancouver
Silva J de A, Hruschka ER. Extending k-means-based algorithms for evolving data streams with variable number of clusters [Internet]. Proceedings. 2011 ;[citado 2026 jan. 20 ] Available from: https://doi.org/10.1109/ICMLA.2011.67 - An optimization framework for combining ensembles of classifiers and clusterers with applications to nontransductive semisupervised learning and transfer learning
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Informações sobre o DOI: 10.1109/ICMLA.2011.67 (Fonte: oaDOI API)
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