Maione, Camila; Barbosa Junior, Fernando 
; Barbosa, Rommel Melgaço
Fonte: Computers and Electronics in Agriculture. Unidade: FCFRP
Assuntos: ANÁLISE DE DADOS, APRENDIZADO COMPUTACIONAL, ADULTERAÇÃO DE ALIMENTOS, MEL
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MAIONE, Camila e BARBOSA JUNIOR, Fernando e BARBOSA, Rommel Melgaço. Predicting the botanical and geographical origin of honey with multivariate data analysis and machine learning techniques: a review. Computers and Electronics in Agriculture, v. 157, p. 436-446, 2019Tradução . . Disponível em: https://doi.org/10.1016/j.compag.2019.01.020. Acesso em: 06 nov. 2024.APA
Maione, C., Barbosa Junior, F., & Barbosa, R. M. (2019). Predicting the botanical and geographical origin of honey with multivariate data analysis and machine learning techniques: a review. Computers and Electronics in Agriculture, 157, 436-446. doi:10.1016/j.compag.2019.01.020NLM
Maione C, Barbosa Junior F, Barbosa RM. Predicting the botanical and geographical origin of honey with multivariate data analysis and machine learning techniques: a review [Internet]. Computers and Electronics in Agriculture. 2019 ; 157 436-446.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.compag.2019.01.020Vancouver
Maione C, Barbosa Junior F, Barbosa RM. Predicting the botanical and geographical origin of honey with multivariate data analysis and machine learning techniques: a review [Internet]. Computers and Electronics in Agriculture. 2019 ; 157 436-446.[citado 2024 nov. 06 ] Available from: https://doi.org/10.1016/j.compag.2019.01.020
