Improved support vector machine classification for imbalanced medical datasets by novel hybrid sampling combining modified mega-trend-diffusion and bagging extreme learning machine model

Improved support vector machine classification for imbalanced medical datasets by novel hybrid sampling combining modified mega-trend-diffusion and bagging extreme learning machine model

To handle imbalanced datasets in machine learning or deep learning models, some studies suggest sampling techniques to generate virtual examples of minority classes to improve the models' prediction accuracy. However, for kernel-based support vector machines (SVM), some sampling methods suggest...

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Bibliographic Details
Main Authors: Liang-Sian Lin, Chen-Huan Kao, Yi-Jie Li, Hao-Hsuan Chen, Hung-Yu Chen
Format: Article
Language:English
Published: AIMS Press 2023-09-01
Series:Mathematical Biosciences and Engineering
Subjects:
imbalanced datasets
hybrid sampling approach
support vectors
virtual examples
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023786?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2023786?viewType=HTML

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