Logic-Based Roughification

摘要: The current chapter is devoted to roughification. In the most general setting, we intend term roughification refer methods/techniques of constructing equivalence/similarity relations adequate for Pawlak-like approximations. Such techniques are fundamental in rough set theory. We propose and investigate novel techniques. show that using proposed one can often discern objects indiscernible by original similarity relations, what results improving also discuss applications granulating relational databases concept learning. last application particularly interesting, as it shows an approach learning which more than approaches based solely on information decision systems.