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Semi-Supervised Fuzzy Clustering with Feature Discrimination
Semi-supervised clustering algorithms are increasingly employed for discovering hidden structure in data with partially labelled patterns. In order to make the clustering approach useful and acceptable to users, the information provided must be simple, natural and limited in number. To improve recog...
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| Pubblicato in: | PLoS One |
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| Autori principali: | , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science
2015
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4556708/ https://ncbi.nlm.nih.gov/pubmed/26325272 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0131160 |
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