Multiway spectral clustering with out-of-sample extensions through weighted kernel PCA
A new formulation for multiway spectral clustering is proposed. This method corresponds to a weighted kernel principal component analysis (PCA) approach based on primal-dual least-squares support vector machine (LS-SVM) formulations. The formulation allows the extension to out-of-sample points. In t...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 32(2010), 2 vom: 15. Feb., Seite 335-47 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2010
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Online verfügbar |
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