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Semi-supervised oblique predictive clustering trees
Semi-supervised learning combines supervised and unsupervised learning approaches to learn predictive models from both labeled and unlabeled data. It is most appropriate for problems where labeled examples are difficult to obtain but unlabeled examples are readily available (e.g., drug repurposing)....
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| Publicat a: | PeerJ Comput Sci |
|---|---|
| Autors principals: | , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
PeerJ Inc.
2021
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8101547/ https://ncbi.nlm.nih.gov/pubmed/33987461 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.7717/peerj-cs.506 |
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