Fonte: Electronics. Unidade: ICMC
Assuntos: VISUALIZAÇÃO, APRENDIZADO COMPUTACIONAL
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MAZUMDAR, Dipankar e POPOLIN NETO, Mário e PAULOVICH, Fernando Vieira. Random forest similarity maps: a scalable visual representation for global and local interpretation. Electronics, v. 10, p. 1-20, 2021Tradução . . Disponível em: https://doi.org/10.3390/electronics10222862. Acesso em: 09 nov. 2024.APA
Mazumdar, D., Popolin Neto, M., & Paulovich, F. V. (2021). Random forest similarity maps: a scalable visual representation for global and local interpretation. Electronics, 10, 1-20. doi:10.3390/electronics10222862NLM
Mazumdar D, Popolin Neto M, Paulovich FV. Random forest similarity maps: a scalable visual representation for global and local interpretation [Internet]. Electronics. 2021 ; 10 1-20.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/electronics10222862Vancouver
Mazumdar D, Popolin Neto M, Paulovich FV. Random forest similarity maps: a scalable visual representation for global and local interpretation [Internet]. Electronics. 2021 ; 10 1-20.[citado 2024 nov. 09 ] Available from: https://doi.org/10.3390/electronics10222862