Evaluation of multiclass novelty detection algorithms for data streams (2015)
- Authors:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.1109/TKDE.2015.2441713
- Assunto: INTELIGÊNCIA ARTIFICIAL
- Language: Inglês
- Imprenta:
- Publisher place: Los Alamitos
- Date published: 2015
- Source:
- Título: IEEE Transactions on Knowledge and Data Engineering
- ISSN: 1041-4347
- Volume/Número/Paginação/Ano: v. 27, n. 11, p. 2961-2973, Nov. 2015
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
FARIA, Elaine Ribeiro de et al. Evaluation of multiclass novelty detection algorithms for data streams. IEEE Transactions on Knowledge and Data Engineering, v. No 2015, n. 11, p. 2961-2973, 2015Tradução . . Disponível em: https://doi.org/10.1109/TKDE.2015.2441713. Acesso em: 04 fev. 2026. -
APA
Faria, E. R. de, Gonçalves, I. R., Gama, J., & Carvalho, A. C. P. de L. F. de. (2015). Evaluation of multiclass novelty detection algorithms for data streams. IEEE Transactions on Knowledge and Data Engineering, No 2015( 11), 2961-2973. doi:10.1109/TKDE.2015.2441713 -
NLM
Faria ER de, Gonçalves IR, Gama J, Carvalho ACP de LF de. Evaluation of multiclass novelty detection algorithms for data streams [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2015 ; No 2015( 11): 2961-2973.[citado 2026 fev. 04 ] Available from: https://doi.org/10.1109/TKDE.2015.2441713 -
Vancouver
Faria ER de, Gonçalves IR, Gama J, Carvalho ACP de LF de. Evaluation of multiclass novelty detection algorithms for data streams [Internet]. IEEE Transactions on Knowledge and Data Engineering. 2015 ; No 2015( 11): 2961-2973.[citado 2026 fev. 04 ] Available from: https://doi.org/10.1109/TKDE.2015.2441713 - Gabinete pequeno é destaque de pc itautec
- New data strucutre and spanning forest operators for evolutionay algorithms
- Metalearning for context-aware filtering: selection of tensor factorization algorithms
- Evolutionary tuning of SVM parameter values in multiclass problems
- Dimensionality reduction for the algorithm recommendation problem
- Making data stream classification tree-based ensembles lighter
- A study of biclustering coherence measures for gene expression data
- Anomaly detection through temporal abstractions on intensive care data: position paper
- CF4CF: recommending collaborative filtering algorithms using collaborative filtering
- A machine learning-based approach for prediction of plant protection product deposition
Informações sobre o DOI: 10.1109/TKDE.2015.2441713 (Fonte: oaDOI API)
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
