Robust clustering algorithms
This thesis focuses on developing a few robust learning algorithms, which aim to overcome the major drawbacks of traditional clustering methods, for data clustering and its extensions.
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2008
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| Online Access: | https://hdl.handle.net/10356/3847 |
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| Institution: | Nanyang Technological University |
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sg-ntu-dr.10356-38472023-07-04T17:13:22Z Robust clustering algorithms Yang, Xulei Song Qing School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This thesis focuses on developing a few robust learning algorithms, which aim to overcome the major drawbacks of traditional clustering methods, for data clustering and its extensions. DOCTOR OF PHILOSOPHY (EEE) 2008-09-17T09:38:53Z 2008-09-17T09:38:53Z 2005 2005 Thesis Yang, X. (2005). Robust clustering algorithms. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/3847 10.32657/10356/3847 Nanyang Technological University application/pdf |
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Nanyang Technological University |
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NTU Library |
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Asia |
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Singapore Singapore |
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NTU Library |
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DR-NTU |
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DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems |
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DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Yang, Xulei Robust clustering algorithms |
| description |
This thesis focuses on developing a few robust learning algorithms, which aim to overcome the major drawbacks of traditional clustering methods, for data clustering and its extensions. |
| author2 |
Song Qing |
| author_facet |
Song Qing Yang, Xulei |
| format |
Theses and Dissertations |
| author |
Yang, Xulei |
| author_sort |
Yang, Xulei |
| title |
Robust clustering algorithms |
| title_short |
Robust clustering algorithms |
| title_full |
Robust clustering algorithms |
| title_fullStr |
Robust clustering algorithms |
| title_full_unstemmed |
Robust clustering algorithms |
| title_sort |
robust clustering algorithms |
| publishDate |
2008 |
| url |
https://hdl.handle.net/10356/3847 |
| _version_ |
1772827231873138688 |