2CS: correlation-guided split candidate selection in Hoeffding tree regressors (2020)
- Authors:
- USP affiliated authors: CARVALHO, ANDRÉ CARLOS PONCE DE LEON FERREIRA DE - ICMC ; MASTELINI, SAULO MARTIELLO - ICMC
- Unidade: ICMC
- DOI: 10.1007/978-3-030-61380-8_23
- Subjects: APRENDIZADO COMPUTACIONAL; ANÁLISE DE SÉRIES TEMPORAIS; ALGORITMOS ÚTEIS E ESPECÍFICOS
- Keywords: Hoeffding trees; Online regression; Data stream mining; Split decisions; Incremental learning
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título: Lecture Notes in Artificial Intelligence
- ISSN: 0302-9743
- Volume/Número/Paginação/Ano: v. 12320, p. 337-351, 2020
- Conference titles: Brazilian Conference on Intelligent Systems - BRACIS
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
MASTELINI, Saulo Martiello e CARVALHO, André Carlos Ponce de Leon Ferreira de. 2CS: correlation-guided split candidate selection in Hoeffding tree regressors. Lecture Notes in Artificial Intelligence. Cham: Springer. Disponível em: https://doi.org/10.1007/978-3-030-61380-8_23. Acesso em: 27 dez. 2025. , 2020 -
APA
Mastelini, S. M., & Carvalho, A. C. P. de L. F. de. (2020). 2CS: correlation-guided split candidate selection in Hoeffding tree regressors. Lecture Notes in Artificial Intelligence. Cham: Springer. doi:10.1007/978-3-030-61380-8_23 -
NLM
Mastelini SM, Carvalho ACP de LF de. 2CS: correlation-guided split candidate selection in Hoeffding tree regressors [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 337-351.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_23 -
Vancouver
Mastelini SM, Carvalho ACP de LF de. 2CS: correlation-guided split candidate selection in Hoeffding tree regressors [Internet]. Lecture Notes in Artificial Intelligence. 2020 ; 12320 337-351.[citado 2025 dez. 27 ] Available from: https://doi.org/10.1007/978-3-030-61380-8_23 - Fast and lightweight binary and multi-branch Hoeffding tree regressors
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Informações sobre o DOI: 10.1007/978-3-030-61380-8_23 (Fonte: oaDOI API)
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