Self-Trained LMT for Semisupervised Learning

The most important asset of semisupervised classification methods is the use of available unlabeled data combined with a clearly smaller set of labeled examples, so as to increase the classification accuracy compared with the default procedure of supervised methods, which on the other hand use only...

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Detalles Bibliográficos
Autores principales: Fazakis, Nikos, Karlos, Stamatis, Kotsiantis, Sotiris, Sgarbas, Kyriakos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709606/
https://www.ncbi.nlm.nih.gov/pubmed/26839531
http://dx.doi.org/10.1155/2016/3057481

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4709606/
https://www.ncbi.nlm.nih.gov/pubmed/26839531
http://dx.doi.org/10.1155/2016/3057481

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