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This paper describes methods for reasoning with unknown, irrelevant, and not-applicable meta-values when learning concept descriptions from examples or discovering patterns in data. These types of meta-values represent different reasons for which regular values are not available, thus require different treatment in both rule learning and rule testing. The presented methods are handled internally,...
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