Li, Yuhua and Pont, Michael J (2002) Improving the performance of radial basis function classifiers in condition monitoring and fault diagnosis applications where 'unknown' faults may occur. Pattern Recognition Letter, 23 (5). pp. 569-577. [Journal article]
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This paper develops a technique for determining a reliable threshold for RBF classifiers. A two-phase approach is proposed to RBF classifier use in situations where unknown faults may occur: the first phase deals with the possibility of unknown faults; in the second phase, the classifier threshold is modified through retraining using all available data, including newly collected data about unknown faults. The approach is easy to use and is demonstrated to be particularly effective in classification problems where novelty detection capability is required.
|Item Type:||Journal article|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Intelligent Systems Research Centre
|Deposited By:||Dr Yuhua Li|
|Deposited On:||03 Feb 2010 11:28|
|Last Modified:||09 May 2016 10:55|
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