Kernel machines and classifier ensemble learning for biomedical applications
This thesis addressed a type of imbalanced data problem encountered in many biomedical applications where one category of data is compactly clustered and the other category of data is scattered in the input space. A new Hybrid Kernel Machine Ensemble (HKME) is proposed to address this problem by int...
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| Format: | Thesis |
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2008
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| Online Access: | https://hdl.handle.net/10356/3452 |
| _version_ | 1826111094953869312 |
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| author | Peng, Li |
| author2 | Shankar M. Krishnan |
| author_facet | Shankar M. Krishnan Peng, Li |
| author_sort | Peng, Li |
| collection | NTU |
| description | This thesis addressed a type of imbalanced data problem encountered in many biomedical applications where one category of data is compactly clustered and the other category of data is scattered in the input space. A new Hybrid Kernel Machine Ensemble (HKME) is proposed to address this problem by integrating a two-class discriminative Support Vector Machine (SVM) and a one-class recognition-based SVM. |
| first_indexed | 2024-10-01T02:45:00Z |
| format | Thesis |
| id | ntu-10356/3452 |
| institution | Nanyang Technological University |
| last_indexed | 2024-10-01T02:45:00Z |
| publishDate | 2008 |
| record_format | dspace |
| spelling | ntu-10356/34522023-07-04T16:55:56Z Kernel machines and classifier ensemble learning for biomedical applications Peng, Li Shankar M. Krishnan Chan, Kap Luk School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics This thesis addressed a type of imbalanced data problem encountered in many biomedical applications where one category of data is compactly clustered and the other category of data is scattered in the input space. A new Hybrid Kernel Machine Ensemble (HKME) is proposed to address this problem by integrating a two-class discriminative Support Vector Machine (SVM) and a one-class recognition-based SVM. DOCTOR OF PHILOSOPHY (EEE) 2008-09-17T09:30:23Z 2008-09-17T09:30:23Z 2006 2006 Thesis Peng, L. (2006). Kernel machines and classifier ensemble learning for biomedical applications. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/3452 10.32657/10356/3452 Nanyang Technological University application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics Peng, Li Kernel machines and classifier ensemble learning for biomedical applications |
| title | Kernel machines and classifier ensemble learning for biomedical applications |
| title_full | Kernel machines and classifier ensemble learning for biomedical applications |
| title_fullStr | Kernel machines and classifier ensemble learning for biomedical applications |
| title_full_unstemmed | Kernel machines and classifier ensemble learning for biomedical applications |
| title_short | Kernel machines and classifier ensemble learning for biomedical applications |
| title_sort | kernel machines and classifier ensemble learning for biomedical applications |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics |
| url | https://hdl.handle.net/10356/3452 |
| work_keys_str_mv | AT pengli kernelmachinesandclassifierensemblelearningforbiomedicalapplications |