Feature scoring using tree-based ensembles for evolving data streams (2019)
- Authors:
- Autor USP: MELLO, RODRIGO FERNANDES DE - ICMC
- Unidade: ICMC
- DOI: 10.1109/BigData47090.2019.9006366
- Subjects: APRENDIZADO COMPUTACIONAL; ANÁLISE DE SÉRIES TEMPORAIS
- Keywords: data streams; feature score; supervised learning; model interpretation
- Language: Inglês
- Imprenta:
- Publisher: IEEE
- Publisher place: Los Alamitos
- Date published: 2019
- Source:
- Título: Proceedings
- Conference titles: IEEE International Conference on Big Data - Big Data
- Status:
- Nenhuma versão em acesso aberto identificada
-
ABNT
GOMES, Heitor Murilo et al. Feature scoring using tree-based ensembles for evolving data streams. 2019, Anais.. Los Alamitos: IEEE, 2019. Disponível em: https://doi.org/10.1109/BigData47090.2019.9006366. Acesso em: 31 mar. 2026. -
APA
Gomes, H. M., Mello, R. F. de, Pfahringer, B., & Bifet, A. (2019). Feature scoring using tree-based ensembles for evolving data streams. In Proceedings. Los Alamitos: IEEE. doi:10.1109/BigData47090.2019.9006366 -
NLM
Gomes HM, Mello RF de, Pfahringer B, Bifet A. Feature scoring using tree-based ensembles for evolving data streams [Internet]. Proceedings. 2019 ;[citado 2026 mar. 31 ] Available from: https://doi.org/10.1109/BigData47090.2019.9006366 -
Vancouver
Gomes HM, Mello RF de, Pfahringer B, Bifet A. Feature scoring using tree-based ensembles for evolving data streams [Internet]. Proceedings. 2019 ;[citado 2026 mar. 31 ] Available from: https://doi.org/10.1109/BigData47090.2019.9006366 - A novel approach to quantify novelty levels applied on ubiquitous music distribution
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