Multi-label Classification Using Vector Generalized Additive Model via Cross-Validation
Multi-label classification is a unique challenge in machine learning designed for two targets with each containing one or multiple classes. This problem can be resolved using several methods, including the classification of the targets individually or simultaneously. However, most models cannot clas...
| 主要な著者: | , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Universiti Utara Malaysia Press
2023
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| 主題: | |
| オンライン･アクセス: | https://repo.uum.edu.my/id/eprint/29908/1/JICT%2022%2004%202023%20657-673.pdf https://doi.org/10.32890/jict2023.22.4.5 |