Principal component analysis: a natural approach to data exploration (2021)
Fonte: ACM Computing Surveys. Unidades: ICMC, IFSC, IF, IME
Assuntos: APRENDIZADO COMPUTACIONAL, VISUALIZAÇÃO, COMPONENTES PRINCIPAIS, ANÁLISE DE COVARIÂNCIA, ANÁLISE DE CORRESPONDÊNCIA
ABNT
GEWERS, Felipe Lucas et al. Principal component analysis: a natural approach to data exploration. ACM Computing Surveys, v. 54, n. 4, p. 70:1-70:34, 2021Tradução . . Disponível em: https://doi.org/10.1145/3447755. Acesso em: 31 out. 2024.APA
Gewers, F. L., Ferreira, G. R., Arruda, H. F. de, Silva, F. N., Comin, C. H., Amancio, D. R., & Costa, L. da F. (2021). Principal component analysis: a natural approach to data exploration. ACM Computing Surveys, 54( 4), 70:1-70:34. doi:10.1145/3447755NLM
Gewers FL, Ferreira GR, Arruda HF de, Silva FN, Comin CH, Amancio DR, Costa L da F. Principal component analysis: a natural approach to data exploration [Internet]. ACM Computing Surveys. 2021 ; 54( 4): 70:1-70:34.[citado 2024 out. 31 ] Available from: https://doi.org/10.1145/3447755Vancouver
Gewers FL, Ferreira GR, Arruda HF de, Silva FN, Comin CH, Amancio DR, Costa L da F. Principal component analysis: a natural approach to data exploration [Internet]. ACM Computing Surveys. 2021 ; 54( 4): 70:1-70:34.[citado 2024 out. 31 ] Available from: https://doi.org/10.1145/3447755