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...
Saved in:
Main Author: | Peng, Li |
---|---|
Other Authors: | Shankar M. Krishnan |
Format: | Theses and Dissertations |
Published: |
2008
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/3452 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Similar Items
-
Support vector machines for biomedical applications
by: Chaw, Su Khine.
Published: (2008) -
Development of an ensemble of extreme learning machines for 3D medical object segmentation and classification
by: Tan, Zu Ming.
Published: (2012) -
Global optimization and biomedical applications
by: Ye, Hong
Published: (2008) -
Development of implantable MEMS for biomedical applications
by: Tng, Danny Jian Hang.
Published: (2012) -
Ultra-wideband (UWB) in biomedical applications
by: Teo, Jianqi.
Published: (2012)