Estimating latent relative labeling importances for multi-label learning
In multi-label learning, each instance is associated with multiple labels simultaneously. Most of the existing approaches directly treat each label in a crisp manner, i.e. one class label is either relevant or irrelevant to the instance. However, the latent relative importance of each relevant label...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/143866 |