Hellinger distance-based stable sparse feature selection for high-dimensional class-imbalanced data

BACKGROUND: Feature selection in class-imbalance learning has gained increasing attention in recent years due to the massive growth of high-dimensional class-imbalanced data across many scientific fields. In addition to reducing model complexity and discovering key biomarkers, feature selection is a...

Descripción completa

Detalles Bibliográficos
Autores principales: Fu, Guang-Hui, Wu, Yuan-Jiao, Zong, Min-Jie, Pan, Jianxin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7092448/
https://www.ncbi.nlm.nih.gov/pubmed/32293252
http://dx.doi.org/10.1186/s12859-020-3411-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7092448/
https://www.ncbi.nlm.nih.gov/pubmed/32293252
http://dx.doi.org/10.1186/s12859-020-3411-3

Ejemplares similares