Two stage partial classification for inconsistent and imbalanced classes
Bedingfield, Susan and Smith-Miles, Kate 2006, Two stage partial classification for inconsistent and imbalanced classes, in Sustainable Development Through Effective Man-Machine Co-Existence: Proceedings of the International Conference on Information and Automation (ICA`06), Institute of Electrical and Electronics Engineers, Piscataway, N.J., pp. 167-171.
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Title
Two stage partial classification for inconsistent and imbalanced classes
Sustainable Development Through Effective Man-Machine Co-Existence: Proceedings of the International Conference on Information and Automation (ICA`06)
Editor(s)
Institute of Electrical and Electronics Engineers
Publication date
2006
Conference series
International Conference on Information and Automation
Start page
167
End page
171
Publisher
Institute of Electrical and Electronics Engineers
Place of publication
Piscataway, N.J.
Summary
When deriving classification rules for a non-symmetric database with a binary target class, it is common practice to generate rules for the majority class, then any object which is not covered by a rule of suitable accuracy is by default given the minority class prediction. However, in the case where misclassification costs for the minority class significantly outweigh those of the majority class, this may mean that there are still costly incorrect predictions. We examine the capability of an evolutionary algorithm to detect these potentially costly misclassifications.
ISBN
1424405556 9781424405558
Language
eng
Field of Research
089999 Information and Computing Sciences not elsewhere classified