Cargando…
A Comparative Study of the Use of Stratified Cross-Validation and Distribution-Balanced Stratified Cross-Validation in Imbalanced Learning
Nowadays, the solution to many practical problems relies on machine learning tools. However, compiling the appropriate training data set for real-world classification problems is challenging because collecting the right amount of data for each class is often difficult or even impossible. In such cas...
Autores principales: | Szeghalmy, Szilvia, Fazekas, Attila |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967638/ https://www.ncbi.nlm.nih.gov/pubmed/36850931 http://dx.doi.org/10.3390/s23042333 |
Ejemplares similares
-
Stratifying primary Sjögren’s syndrome: killers in the balance?
por: Bowman, Simon J., et al.
Publicado: (2015) -
Stratifying the stratifiers of triple negative breast cancer
por: Wang, Dong-Yu, et al.
Publicado: (2020) -
Stratified polyhedra
por: Stone, David A
Publicado: (1972) -
Stratified flows
por: Yih, Chia-Shun
Publicado: (1980) -
Validating and Comparing C-TIRADS, K-TIRADS and ACR-TIRADS in Stratifying the Malignancy Risk of Thyroid Nodules
por: Chen, Qingfang, et al.
Publicado: (2022)