Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Tanapol Kosolwattana"'
Publikováno v:
BioData Mining, Vol 16, Iss 1, Pp 1-14 (2023)
Abstract In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease onset. The SMOTE (Synthetic Minority Over-sampling Technique) algorithm has been developed as a
Externí odkaz:
https://doaj.org/article/01f80239ddd7418fb1740080527958fc
In many healthcare applications, datasets for classification may be highly imbalanced due to the rare occurrence of target events such as disease onset. The SMOTE (Synthetic Minority Over-sampling Technique) algorithm has been developed as an effecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::db8e5413a05fdcedaf2a9cd44b448c17
https://doi.org/10.21203/rs.3.rs-1647776/v1
https://doi.org/10.21203/rs.3.rs-1647776/v1
Publikováno v:
ACM Computing Surveys; Jan2025, Vol. 57 Issue 1, p1-48, 48p
Autor:
Kosolwattana, Tanapol1 (AUTHOR), Liu, Chenang2 (AUTHOR), Hu, Renjie3 (AUTHOR), Han, Shizhong4,5 (AUTHOR), Chen, Hua6 (AUTHOR), Lin, Ying1 (AUTHOR) ylin58@uh.edu
Publikováno v:
BioData Mining. 4/25/2023, Vol. 16 Issue 1, p1-14. 14p.