Combining data-driven and user-driven evaluation measures to identify intersting rules (2009)
Rezende, Solange Oliveira 
; Melanda, Edson Augusto; Fujimoto, Magaly Lika; Sinoara, Roberta Akemi; Carvalho, Veronica Oliveira de
Source: Post-mining of association rules : techniques for effective knowledge extraction. Unidade: ICMC
Assunto: INTELIGÊNCIA ARTIFICIAL
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ABNT
REZENDE, Solange Oliveira et al. Combining data-driven and user-driven evaluation measures to identify intersting rules. Post-mining of association rules : techniques for effective knowledge extraction. Tradução . Hershey: Information Science Reference, 2009. . . Acesso em: 08 nov. 2024.APA
Rezende, S. O., Melanda, E. A., Fujimoto, M. L., Sinoara, R. A., & Carvalho, V. O. de. (2009). Combining data-driven and user-driven evaluation measures to identify intersting rules. In Post-mining of association rules : techniques for effective knowledge extraction. Hershey: Information Science Reference.NLM
Rezende SO, Melanda EA, Fujimoto ML, Sinoara RA, Carvalho VO de. Combining data-driven and user-driven evaluation measures to identify intersting rules. In: Post-mining of association rules : techniques for effective knowledge extraction. Hershey: Information Science Reference; 2009. [citado 2024 nov. 08 ]Vancouver
Rezende SO, Melanda EA, Fujimoto ML, Sinoara RA, Carvalho VO de. Combining data-driven and user-driven evaluation measures to identify intersting rules. In: Post-mining of association rules : techniques for effective knowledge extraction. Hershey: Information Science Reference; 2009. [citado 2024 nov. 08 ]
