An experimental evaluation of simplicity in rule learning
Artificial Intelligence
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In this report, the prediction performances of two rule evaluation measures, accuracy and weighted relative accuracy, are compared. These two measures were used in two different versions of CN2 algorithm for inducing classification rules. The first version (CN2-acc) is the original one, where the accuracy measure for evaluating rules is used. The second one (CN2-wracc) uses weighted relative accuracy. The performance of two versions of CN2 was compared in sense of classification accuracy as well as number and length of the induced rules.