Parameter-Insensitive Min Cut Clustering With Flexible Size Constrains
Clustering is a fundamental topic in machine learning and various methods are proposed, in which K-Means (KM) and min cut clustering are typical ones. However, they may produce empty or skewed clustering results, which are not as expected. In KM, the constrained clustering methods have been fully st...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 8 vom: 19. Juli, Seite 5479-5492 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2024
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article |
| Online verfügbar |
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