A study of the correlation of metafeatures used for metalearning (2021)
- Authors:
- Autor USP: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-030-85030-2_39
- Subjects: APRENDIZADO COMPUTACIONAL; ALGORITMOS ÚTEIS E ESPECÍFICOS
- Keywords: Metalearning; Metafeature; Characterization measures; Metafeature selection
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Lecture Notes in Computer Science
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 12861, p. 471-483, 2021
- Conference titles: International Work-Conference on Artificial Neural Networks - IWANN
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
RIVOLLI, Adriano et al. A study of the correlation of metafeatures used for metalearning. Lecture Notes in Computer Science. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-85030-2_39. Acesso em: 24 fev. 2026. , 2021 -
APA
Rivolli, A., Garcia, L. P. F., Lorena, A. C., & Carvalho, A. C. P. de L. F. de. (2021). A study of the correlation of metafeatures used for metalearning. Lecture Notes in Computer Science. Cham: Springer. doi:10.1007/978-3-030-85030-2_39 -
NLM
Rivolli A, Garcia LPF, Lorena AC, Carvalho ACP de LF de. A study of the correlation of metafeatures used for metalearning [Internet]. Lecture Notes in Computer Science. 2021 ; 12861 471-483.[citado 2026 fev. 24 ] Available from: https://doi.org/10.1007/978-3-030-85030-2_39 -
Vancouver
Rivolli A, Garcia LPF, Lorena AC, Carvalho ACP de LF de. A study of the correlation of metafeatures used for metalearning [Internet]. Lecture Notes in Computer Science. 2021 ; 12861 471-483.[citado 2026 fev. 24 ] Available from: https://doi.org/10.1007/978-3-030-85030-2_39 - 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: 10.1007/978-3-030-85030-2_39 (Fonte: oaDOI API)
Download do texto completo
| Tipo | Nome | Link | |
|---|---|---|---|
 |
3044284.pdf |
How to cite
A citação é gerada automaticamente e pode não estar totalmente de acordo com as normas
