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

Zhaozhao Xu; Derong Shen; Tiezheng Nie; Yue Kou

doi:10.1016/j.jbi.2020.103465

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

Zhaozhao Xu Derong Shen Tiezheng Nie Yue Kou

Year: 2020 Journal: Journal of Biomedical Informatics Vol: 107 Pages: 103465-103465 Publisher: Elsevier BV

DOI: 10.1016/j.jbi.2020.103465

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Keywords:

Random forest Computer science Oversampling Sampling (signal processing) Artificial intelligence Data mining Identification (biology) Algorithm Statistical classification Pattern recognition (psychology) Machine learning

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Imbalanced Data Classification Techniques

Physical Sciences → Computer Science → Artificial Intelligence

Artificial Intelligence in Healthcare

Health Sciences → Health Professions → Health Information Management

Electricity Theft Detection Techniques

Physical Sciences → Engineering → Electrical and Electronic Engineering

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

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