A cluster-based hybrid sampling approach for imbalanced data classification
Author:
Affiliation:
1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2. School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
Funder
National Natural Science Foundation of China
Publisher
AIP Publishing
Subject
Instrumentation
Link
http://aip.scitation.org/doi/pdf/10.1063/5.0008935
Reference27 articles.
1. Classification of Imbalanced Data by Oversampling in Kernel Space of Support Vector Machines
2. Classifying imbalanced data sets using similarity based hierarchical decomposition
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4. Research on classification method of high-dimensional class-imbalanced datasets based on SVM
5. Self-Paced Balance Learning for Clinical Skin Disease Recognition
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