Source: Anais. Conference titles: Brazilian Symposium on Data Bases - SBBD. Unidade: ICMC
Subjects: APRENDIZADO COMPUTACIONAL, ANÁLISE MULTIVARIADA
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ABNT
SILVA, Renata Barbosa et al. Criteria for choosing the number of dimensions in a principal component analysis: an empirical assessment. 2020, Anais.. Porto Alegre: SBC, 2020. Disponível em: https://sol.sbc.org.br/index.php/sbbd/article/view/13632. Acesso em: 08 out. 2024.APA
Silva, R. B., Oliveira, D. de, Santos, D. P. dos, Santos, L. F. D., Wilson, R. E., & Bêdo, M. V. N. (2020). Criteria for choosing the number of dimensions in a principal component analysis: an empirical assessment. In Anais. Porto Alegre: SBC. Recuperado de https://sol.sbc.org.br/index.php/sbbd/article/view/13632NLM
Silva RB, Oliveira D de, Santos DP dos, Santos LFD, Wilson RE, Bêdo MVN. Criteria for choosing the number of dimensions in a principal component analysis: an empirical assessment [Internet]. Anais. 2020 ;[citado 2024 out. 08 ] Available from: https://sol.sbc.org.br/index.php/sbbd/article/view/13632Vancouver
Silva RB, Oliveira D de, Santos DP dos, Santos LFD, Wilson RE, Bêdo MVN. Criteria for choosing the number of dimensions in a principal component analysis: an empirical assessment [Internet]. Anais. 2020 ;[citado 2024 out. 08 ] Available from: https://sol.sbc.org.br/index.php/sbbd/article/view/13632