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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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Detalles Bibliográficos
Autores principales: Stepišnik, Tomaž, Kocev, Dragi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8101547/
https://www.ncbi.nlm.nih.gov/pubmed/33987461
http://dx.doi.org/10.7717/peerj-cs.506