Semi-supervised oblique predictive clustering trees
Semi-supervised oblique predictive clustering trees
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Publisher
United States: PeerJ, Inc
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Language
English
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Publisher
United States: PeerJ, Inc
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Contents
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). Semi-supervised predictive clustering trees (SSL-...
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Full title
Semi-supervised oblique predictive clustering trees
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TN_cdi_doaj_primary_oai_doaj_org_article_48ac210817f1400f9562d7232f7d10e2
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_48ac210817f1400f9562d7232f7d10e2
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ISSN
2376-5992
E-ISSN
2376-5992
DOI
10.7717/peerj-cs.506
