An Evaluation of Approaches to Classification Rule Selection

Authors:
Frans Coenen;Paul Leng
Affiliations:
The University of Liverpool, UK;The University of Liverpool, UK
Venue:
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Year:
2004

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Abstract

In this paper a number of Classification Rule evaluation measures are considered. In particular the authors review the use of a variety of selection techniques used to order classification rules contained in a classifier, and a number of mechanisms used to classify unseen data. The authors demonstrate that rule ordering founded on the size of antecedent works well given certain conditions.