A unified framework of density-based clustering for semi-supervised classification (2018)
- Authors:
- Autor USP: CAMPELLO, RICARDO JOSÉ GABRIELLI BARRETO - ICMC
- Unidade: ICMC
- DOI: 10.1145/3221269.3223037
- Subjects: APRENDIZADO COMPUTACIONAL; RECONHECIMENTO DE PADRÕES; ALGORITMOS ÚTEIS E ESPECÍFICOS
- Keywords: Semi-supervised classification; density-based clustering
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Proceedings
- Conference titles: International Conference on Scientific and Statistical Database Management - SSDBM
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
GERTRUDES, Jadson Castro et al. A unified framework of density-based clustering for semi-supervised classification. 2018, Anais.. New York: ACM, 2018. Disponível em: https://doi.org/10.1145/3221269.3223037. Acesso em: 26 abr. 2024. -
APA
Gertrudes, J. C., Zimek, A., Sander, J., & Campello, R. J. G. B. (2018). A unified framework of density-based clustering for semi-supervised classification. In Proceedings. New York: ACM. doi:10.1145/3221269.3223037 -
NLM
Gertrudes JC, Zimek A, Sander J, Campello RJGB. A unified framework of density-based clustering for semi-supervised classification [Internet]. Proceedings. 2018 ;[citado 2024 abr. 26 ] Available from: https://doi.org/10.1145/3221269.3223037 -
Vancouver
Gertrudes JC, Zimek A, Sander J, Campello RJGB. A unified framework of density-based clustering for semi-supervised classification [Internet]. Proceedings. 2018 ;[citado 2024 abr. 26 ] Available from: https://doi.org/10.1145/3221269.3223037 - Robust expansion of uncertain Volterra kernels into orthonormal series
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- Automatic aspect discrimination in data clustering
- Identificação e controle de processos via desenvolvimentos em séries ortonormais: parte B: controle preditivo
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- Relative validity criteria for community mining algorithms
- Similarity measures for comparing biclusterings
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Informações sobre o DOI: 10.1145/3221269.3223037 (Fonte: oaDOI API)
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