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In this paper, an approach to facilitate the treatment with variabilities in system families is presented by explicitly modelling variants. The proposed method of managing variabi...
Decision table decomposition is a machine learning approach that decomposes a given decision table into an equivalent hierarchy of decision tables. The approach aims to discover d...
In this paper, we introduce a neural network -based decision table algorithm. We focus on the implementation details of the decision table algorithm when it is constructed using t...
As two classical measures, approximation accuracy and consistency degree can be employed to evaluate the decision performance of a decision table. However, these two measures cann...
Classical consistency degree has some limitations for measuring the consistency of a decision table, in which the lower approximation of a target decision is only taken into consi...
A formal equivalence between propositional expert systems and decision tables is proved, and a practicable procedure given to perform the transformation between propositional expe...
— Decision rules generated from reducts can fully describe a data set. We introduce a new method of evaluating rules by taking advantage of rough sets theory. We consider rules g...