Source: Data Mining and Knowledge Discovery. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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CAMPOS, Guilherme O et al. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Mining and Knowledge Discovery, v. 30, n. 4, p. 891-927, 2016Tradução . . Disponível em: https://doi.org/10.1007/s10618-015-0444-8. Acesso em: 27 abr. 2024.APA
Campos, G. O., Zimek, A., Sander, J., Campello, R. J. G. B., Micenková, B., Schubert, E., et al. (2016). On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study. Data Mining and Knowledge Discovery, 30( 4), 891-927. doi:10.1007/s10618-015-0444-8NLM
Campos GO, Zimek A, Sander J, Campello RJGB, Micenková B, Schubert E, Assent I, Houle ME. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 4): 891-927.[citado 2024 abr. 27 ] Available from: https://doi.org/10.1007/s10618-015-0444-8Vancouver
Campos GO, Zimek A, Sander J, Campello RJGB, Micenková B, Schubert E, Assent I, Houle ME. On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study [Internet]. Data Mining and Knowledge Discovery. 2016 ; 30( 4): 891-927.[citado 2024 abr. 27 ] Available from: https://doi.org/10.1007/s10618-015-0444-8
