Multilabel Over-sampling and Under-sampling with Class Alignment for Imbalanced Multilabel Text Classification
Simultaneous multiple labelling of documents, also known as multilabel text classification, will not perform optimally if the class is highly imbalanced. Class imbalanced entails skewness in the fundamental data for distribution that leads to more difficulty in classification. Random over-sampling a...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Utara Malaysia Press
2021
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| Subjects: | |
| Online Access: | https://repo.uum.edu.my/id/eprint/28781/1/JICT%2020%2003%202021%20423-456.pdf |