A comparison of classification strategies in rule-based classifiers
Szymon Wojciechowski · Logic Journal of IGPL · 2017
This article discusses classification strategies in rule-based classifiers, reveals how often induced rules did not lead to unambiguous classification and emphasizes a major role that classification strategies play in classification of unknown examples. Five selected popular classification strategies proposed by Michalski |$et al$|, Grzymała-Busse and Zou, An, Stefanowski, Sulzmann and Fürnkranz are reviewed and compared experimentally. Additionally, a new strategy that exploits |$\chi^{2}$| statistic to measure the association between the rule coverage and the indicated class is proposed. The experiment was conducted on 30 UCI datasets using MODLEM and modified RIPPER classifiers.