In the context of generalized rough sets, it is possible to introduce in an Information System two different rough approximations. These are induced, respectively, by a Similarity and a Preclusivity relation. It is possible to show that the last one is always better than the first one. Here, we present a quantitative analysis of the relative performances of the two different approximations. The most important conclusion is that preclusive and similar approximation consistently differ when there is a low quality of approximation
Cattaneo, G., Ciucci, D. (2002). A quantitative analysis of preclusivity vs. similarity based rough approximation. In Rough Sets and Current Trends in Computing, Third International Conference, RSCTC 2002 (pp.69-76). Springer [10.1007/3-540-45813-1_9].
A quantitative analysis of preclusivity vs. similarity based rough approximation
CATTANEO, GIANPIERO;CIUCCI, DAVIDE ELIO
2002
Abstract
In the context of generalized rough sets, it is possible to introduce in an Information System two different rough approximations. These are induced, respectively, by a Similarity and a Preclusivity relation. It is possible to show that the last one is always better than the first one. Here, we present a quantitative analysis of the relative performances of the two different approximations. The most important conclusion is that preclusive and similar approximation consistently differ when there is a low quality of approximation
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