Abstract. We provide the unified methodology for searching for approximate decision reducts based on rough membership distributions. Presented study generalizes well known relation...
The optimization of rough set based classification models with respect to parameterized balance between a model's complexity and confidence is discussed. For this purpose, the...
The original rough-set model is primarily concerned with the approximations of sets described by a single equivalence relation on a given universe. With granular computing point of...
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...
We use information entropy measure to extend the rough set based notion of a reduct. We introduce the Approximate Entropy Reduction Principle (AERP). It states that any simplificat...