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https://hdl.handle.net/10356/3452
Title: | Kernel machines and classifier ensemble learning for biomedical applications | Authors: | Peng, Li | Keywords: | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation::Medical electronics | Issue Date: | 2006 | Source: | Peng, L. (2006). Kernel machines and classifier ensemble learning for biomedical applications. Doctoral thesis, Nanyang Technological University, Singapore. | Abstract: | 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. | URI: | https://hdl.handle.net/10356/3452 | DOI: | 10.32657/10356/3452 | Schools: | School of Electrical and Electronic Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Theses |
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EEE-THESES_1312.pdf | 8.33 MB | Adobe PDF | View/Open |
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