Performance evaluation of outlier rules for labelling outliers in multidimensional dataset (2021)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; SILVA, KELLY CRISTINA RAMOS DA - ICMC
- Unidade: ICMC
- DOI: 10.1504/IJBIDM.2021.117111
- Subjects: RECONHECIMENTO DE PADRÕES; MINERAÇÃO DE DADOS; ALGORITMOS ÚTEIS E ESPECÍFICOS
- Keywords: outlier detection; outlier rule; evaluation measure; boxplot; adjusted boxplot; k-NN
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: International Journal of Business Intelligence and Data Mining
- ISSN: 1743-8187
- Volume/Número/Paginação/Ano: v. 19, n. 2, p. 135-152, 2021
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SILVA, Kelly Cristina Ramos da e OLIVEIRA, Helder Luiz Costa de e CARVALHO, André Carlos Ponce de Leon Ferreira de. Performance evaluation of outlier rules for labelling outliers in multidimensional dataset. International Journal of Business Intelligence and Data Mining, v. 19, n. 2, p. 135-152, 2021Tradução . . Disponível em: https://doi.org/10.1504/IJBIDM.2021.117111. Acesso em: 15 fev. 2026. -
APA
Silva, K. C. R. da, Oliveira, H. L. C. de, & Carvalho, A. C. P. de L. F. de. (2021). Performance evaluation of outlier rules for labelling outliers in multidimensional dataset. International Journal of Business Intelligence and Data Mining, 19( 2), 135-152. doi:10.1504/IJBIDM.2021.117111 -
NLM
Silva KCR da, Oliveira HLC de, Carvalho ACP de LF de. Performance evaluation of outlier rules for labelling outliers in multidimensional dataset [Internet]. International Journal of Business Intelligence and Data Mining. 2021 ; 19( 2): 135-152.[citado 2026 fev. 15 ] Available from: https://doi.org/10.1504/IJBIDM.2021.117111 -
Vancouver
Silva KCR da, Oliveira HLC de, Carvalho ACP de LF de. Performance evaluation of outlier rules for labelling outliers in multidimensional dataset [Internet]. International Journal of Business Intelligence and Data Mining. 2021 ; 19( 2): 135-152.[citado 2026 fev. 15 ] Available from: https://doi.org/10.1504/IJBIDM.2021.117111 - Robust outlier labeling rules for light-tailed and heavy-tailed Data
- 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
Informações sobre o DOI: 10.1504/IJBIDM.2021.117111 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
| 3040838_postprint.pdf | Direct link |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
