Data stream classification guided by clustering on nonstationary environments and extreme verification latency (2015)
- Authors:
- Autor USP: BATISTA, GUSTAVO ENRIQUE DE ALMEIDA PRADO ALVES - ICMC
- Unidade: ICMC
- DOI: 10.1137/1.9781611974010.98
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher: SIAM
- Publisher place: Philadelphia
- Date published: 2015
- Source:
- Título: Proceedings
- Conference titles: SIAM International Conference on Data Mining - SDM
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SOUZA, Vinícius M. A et al. Data stream classification guided by clustering on nonstationary environments and extreme verification latency. 2015, Anais.. Philadelphia: SIAM, 2015. Disponível em: https://doi.org/10.1137/1.9781611974010.98. Acesso em: 23 fev. 2026. -
APA
Souza, V. M. A., Silva, D. F., Gama, J., & Batista, G. E. de A. P. A. (2015). Data stream classification guided by clustering on nonstationary environments and extreme verification latency. In Proceedings. Philadelphia: SIAM. doi:10.1137/1.9781611974010.98 -
NLM
Souza VMA, Silva DF, Gama J, Batista GE de APA. Data stream classification guided by clustering on nonstationary environments and extreme verification latency [Internet]. Proceedings. 2015 ;[citado 2026 fev. 23 ] Available from: https://doi.org/10.1137/1.9781611974010.98 -
Vancouver
Souza VMA, Silva DF, Gama J, Batista GE de APA. Data stream classification guided by clustering on nonstationary environments and extreme verification latency [Internet]. Proceedings. 2015 ;[citado 2026 fev. 23 ] Available from: https://doi.org/10.1137/1.9781611974010.98 - Time series classification with motifs and characteristics
- Uma avaliação sobre a identificação de Motifs em séries temporais
- A fuzzy classifier for data streams with infinitely delayed labels
- Fast unsupervised online drift detection using incremental Kolmogorov-Smirnov test
- A complexity-invariant measure based on fractal dimension for time series classification
- Towards automatic classification on flying insects using inexpensive sensors
- Data mining a trillion time series subsequences under dynamic time warping
- Distância invariante à complexidade baseada em dimensão fractal para classificação de séries temporais
- Unsupervised context switch for classification tasks on data streams with recurrent concepts
- On the need of class ratio insensitive drift tests for data streams
Informações sobre o DOI: 10.1137/1.9781611974010.98 (Fonte: oaDOI API)
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