Imbalanced Data Classification Method Based on LSSASMOTE
Imbalanced data exist extensively in the real world, and the classification of imbalanced data is a hot topic in machine learning. In order to classify imbalanced data more effectively, an oversampling method named LSSASMOTE is proposed in this paper. First, the kernel function parameters and penalt...
Main Authors: | Zhi Wang, Qicheng Liu |
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Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10082915/ |
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