Towards meta-learning for multi-target regression problems (2019)
- Authors:
- Autor USP: MASTELINI, SAULO MARTIELLO - ICMC
- Unidade: ICMC
- DOI: 10.1109/BRACIS.2019.00073
- Subjects: APRENDIZADO COMPUTACIONAL; MATEMÁTICA DA COMPUTAÇÃO
- Keywords: Multi-target; Regression; Meta-learning
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Piscataway
- Date published: 2019
- Source:
- Título: Proceedings
- ISSN: 2643-6264
- Conference titles: Brazilian Conference on Intelligent Systems - BRACIS
- Este periódico é de assinatura
- Este artigo é de acesso aberto
- URL de acesso aberto
- Cor do Acesso Aberto: green
-
ABNT
AGUIAR, Gabriel Jones et al. Towards meta-learning for multi-target regression problems. 2019, Anais.. Piscataway: IEEE, 2019. Disponível em: https://doi.org/10.1109/BRACIS.2019.00073. Acesso em: 26 dez. 2025. -
APA
Aguiar, G. J., Santana, E. J., Mastelini, S. M., Mantovani, R. G., & Barbon Júnior, S. (2019). Towards meta-learning for multi-target regression problems. In Proceedings. Piscataway: IEEE. doi:10.1109/BRACIS.2019.00073 -
NLM
Aguiar GJ, Santana EJ, Mastelini SM, Mantovani RG, Barbon Júnior S. Towards meta-learning for multi-target regression problems [Internet]. Proceedings. 2019 ;[citado 2025 dez. 26 ] Available from: https://doi.org/10.1109/BRACIS.2019.00073 -
Vancouver
Aguiar GJ, Santana EJ, Mastelini SM, Mantovani RG, Barbon Júnior S. Towards meta-learning for multi-target regression problems [Internet]. Proceedings. 2019 ;[citado 2025 dez. 26 ] Available from: https://doi.org/10.1109/BRACIS.2019.00073 - Improved prediction of soil properties with multi-target stacked generalisation on EDXRF spectra
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Informações sobre o DOI: 10.1109/BRACIS.2019.00073 (Fonte: oaDOI API)
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