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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...

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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

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