Cargando…
COVER: conformational oversampling as data augmentation for molecules
Training neural networks with small and imbalanced datasets often leads to overfitting and disregard of the minority class. For predictive toxicology, however, models with a good balance between sensitivity and specificity are needed. In this paper we introduce conformational oversampling as a means...
Autores principales: | Hemmerich, Jennifer, Asilar, Ece, Ecker, Gerhard F. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7080709/ https://www.ncbi.nlm.nih.gov/pubmed/33430975 http://dx.doi.org/10.1186/s13321-020-00420-z |
Ejemplares similares
-
Data augmentation based on multiple oversampling fusion for medical image segmentation
por: Wu, Liangsheng, et al.
Publicado: (2022) -
Selective oversampling approach for strongly imbalanced data
por: Gnip, Peter, et al.
Publicado: (2021) -
Iterative Nearest Neighborhood Oversampling in Semisupervised Learning from Imbalanced Data
por: Li, Fengqi, et al.
Publicado: (2013) -
An oversampling method for multi-class imbalanced data based on composite weights
por: Deng, Mingyang, et al.
Publicado: (2021) -
Oversampling delta-sigma data converters: theory, design, and simulation
por: Candy, James C, et al.
Publicado: (1992)