An Integrated Framework of Positive-Unlabeled and Imbalanced Learning for Landslide Susceptibility Mapping
Machine learning is pivotal in data-driven landslide susceptibility mapping (LSM). However, the uncertainty of negative samples and the imbalance between positive and negative samples, which leads to misjudgments and overestimation, remain ongoing challenges. This study introduces a novel framework...
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| Автори: | , , , , , |
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| Формат: | Artigo |
| Мова: | Inglês |
| Опубліковано: |
IEEE
2024-01-01
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| Серія: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Предмети: | |
| Онлайн доступ: | https://ieeexplore.ieee.org/document/10660469/ |
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