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Various algorithms are capable of learning a set of classification rules from a number of observations with their corresponding class labels. Whereas the obtained rule set is usually evaluated by measuring its accuracy on a number of unseen examples, there are several other evaluation criteria, such as comprehensibility and consistency, that are often overlooked. In this paper we focus on the aspect...
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