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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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| Publié dans: | PeerJ Comput Sci |
|---|---|
| Auteurs principaux: | , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
PeerJ Inc.
2021
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| Sujets: | |
| Accès en ligne: | 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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