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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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| Vydáno v: | IEEE Trans Cybern |
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| Hlavní autoři: | , , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
2016
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| Témata: | |
| On-line přístup: | 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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