Maione, Camila; Turra, Christian; Fernandes, Elisabete Aparecida de Nadai 
; Bacchi, Márcio Arruda; Barbosa Junior, Fernando; Barbosa, Rommel Melgaço
Source: Analytical Letters. Unidade: CENA
Subjects: CITRINO, CLASSIFICAÇÃO, MINERAÇÃO DE DADOS, ESPECTROMETRIA DE MASSAS
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MAIONE, Camila et al. Finding the most significant elements for the classification of organic orange leaves a data mining approach: a data mining approach. Analytical Letters, v. 50, n. 14, p. 2292–2307, 2017Tradução . . Disponível em: https://doi.org/10.1080/00032719.2017.1286667. Acesso em: 02 nov. 2024.APA
Maione, C., Turra, C., Fernandes, E. A. de N., Bacchi, M. A., Barbosa Junior, F., & Barbosa, R. M. (2017). Finding the most significant elements for the classification of organic orange leaves a data mining approach: a data mining approach. Analytical Letters, 50( 14), 2292–2307. doi:10.1080/00032719.2017.1286667NLM
Maione C, Turra C, Fernandes EA de N, Bacchi MA, Barbosa Junior F, Barbosa RM. Finding the most significant elements for the classification of organic orange leaves a data mining approach: a data mining approach [Internet]. Analytical Letters. 2017 ; 50( 14): 2292–2307.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1080/00032719.2017.1286667Vancouver
Maione C, Turra C, Fernandes EA de N, Bacchi MA, Barbosa Junior F, Barbosa RM. Finding the most significant elements for the classification of organic orange leaves a data mining approach: a data mining approach [Internet]. Analytical Letters. 2017 ; 50( 14): 2292–2307.[citado 2024 nov. 02 ] Available from: https://doi.org/10.1080/00032719.2017.1286667
