Reject option for VQ-based Bayesian classification
- 11 November 2002
- proceedings article
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 48-51
- https://doi.org/10.1109/icpr.2000.906016
Abstract
We have developed a reject option for VQ-based supervised Bayesian classification to improve classification accuracy by sieving out patterns that are classified with a low confidence value. A small codebook extracted from a learning vector quantizer (LVQ) is used to estimate the class-conditional densities of the feature vector. We adapt the two commonly used rejection criteria, outlier rejection and ambiguity rejection, for the VQ-based Bayesian classifiers. Using three high-level image...Keywords
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