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Partial Classifier Chains with Feature Selection by Exploiting Label Correlation in Multi-Label Classification
Multi-label classification (MLC) is a supervised learning problem where an object is naturally associated with multiple concepts because it can be described from various dimensions. How to exploit the resulting label correlations is the key issue in MLC problems. The classifier chain (CC) is a well-...
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| Publicat a: | Entropy (Basel) |
|---|---|
| Autors principals: | , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
MDPI
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7597295/ https://ncbi.nlm.nih.gov/pubmed/33286912 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e22101143 |
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