Class Weights Random Forest Algorithm for Processing Class Imbalanced Medical Data

Class Weights Random Forest Algorithm for Processing Class Imbalanced Medical Data

The classification in class imbalanced data has drawn significant interest in medical application. Most existing methods are prone to categorize the samples into the majority class, resulting in bias, in particular the insufficient identification of minority class. A kind of novel approach, class we...

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Bibliographic Details
Main Authors: Min Zhu, Jing Xia, Xiaoqing Jin, Molei Yan, Guolong Cai, Jing Yan, Gangmin Ning
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Class imbalanced
random forest
weighted voting
class weights voting
Online Access:https://ieeexplore.ieee.org/document/8246503/

Internet

https://ieeexplore.ieee.org/document/8246503/

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