A hybrid sampling algorithm combining M-SMOTE and ENN based on Random forest for medical imbalanced data.

The problem of imbalanced data classification often exists in medical diagnosis. Traditional classification algorithms usually assume that the number of samples in each class is similar and their misclassification cost during training is equal. However, the misclassification cost of patient samples...

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Detalles Bibliográficos
Publicado en:Journal of Biomedical Informatics Vol. 107
Autores principales: Xu, Zhaozhao, Shen, Derong, Nie, Tiezheng, Kou, Yue
Formato: research Journal Article
Publicado: Academic Press Inc. Jul2020
Acceso en línea:Ver este registro en EBSCOhost