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Attribute reduction is one of the most important topics in rough set theory. In the classical rough sets, the method for attribute reduction is mainly to keep positive region, boundary region, and negative region unchanged. However, the three regions are no longer monotonic with respect to adding or deleting an attribute in decision‐theoretic rough sets. In decision‐theoretic rough set model, the...
The classical rough set attribute reduction is mainly based on maintaining three unvarying regions: positive region, boundary region, and negative region. In the decision rough set model, the reduction procedure for adding or deleting an attribute is no longer monotonous, and as such the three regions will not be kept unchanged simultaneously. In decision theoretic rough set model, cost should be...
The disjunctive model of skill map in knowledge spaces can be interpreted based on an or-binary relation table between skills and questions. There may exist skills that are the union of other skills. Omitting these skills will not change the knowledge structure. Finding a minimal skill set may be formulated similar to the problem of attribute reduction in rough set theory, where an and-binary relation...
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