Clustering-Guided Sparse Structural Learning for Unsupervised Feature Selection
Many pattern analysis and data mining problems have witnessed high-dimensional data represented by a large number of features, which are often redundant and noisy. Feature selection is one main technique for dimensionality reduction that involves identifying a subset of the most useful features. In...
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| Veröffentlicht in: | IEEE transactions on knowledge and data engineering Jg. 26; H. 9; S. 2138 - 2150 |
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| Hauptverfasser: | , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
IEEE
01.09.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Schlagworte: | |
| ISSN: | 1041-4347, 1558-2191 |
| Online-Zugang: | Volltext |
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