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Cluster Prototypes and Fuzzy Memberships Jointly Leveraged Cross-Domain Maximum Entropy Clustering
The classical maximum entropy clustering (MEC) algorithm usually cannot achieve satisfactory results in the situations where the data is insufficient, incomplete, or distorted. To address this problem, inspired by transfer learning, the specific cluster prototypes and fuzzy memberships jointly lever...
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| Pubblicato in: | IEEE Trans Cybern |
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| Autori principali: | , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4882931/ https://ncbi.nlm.nih.gov/pubmed/26684257 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TCYB.2015.2399351 |
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