Using association rules to make rule-based classifiers robust
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(Published version)
Date
2005
Authors
Hu, H.
Li, J.
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Conference paper
Citation
Conferences in Research and Practice in Information Technology Series, 2005, vol.39, pp.47-54
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16th Australasian Database Conference (31 Jan 2005 : Newcastle, New South Wales)
Abstract
Rule-based classification systems have been widely used in real world applications because of the easy interpretability of rules. Many traditional rule-based classifiers prefer small rule sets to large rule sets, but small classifiers are sensitive to the missing values in unseen test data. In this paper, we present a larger classifier that is less sensitive to the missing values in unseen test data. We experimentally show that it is more accurate than some benchmark classifies when unseen test data have missing values.
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Copyright 2005 Australian Computer Society