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Re: [ontolog-forum] Ontology of Rough Sets

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: Tara Athan <taraathan@xxxxxxxxx>
Date: Sat, 15 Jan 2011 03:11:07 -0800
Message-id: <4D3180CB.2050404@xxxxxxxxxx>
Christopher Menzel wrote:
On Jan 14, 2011, at 4:16 PM, Rich Cooper wrote:



Agreed, rough set theory is a different view of sets, not probabilistic, not fuzzy,

Rough sets differ formally from fuzzy sets in some important ways, but they are certainly kissin' cousins.  Both were designed to deal with vagueness and imperfect knowledge, and the idea of the boundary region of a rough set is meant to do the same sort of work that fuzzy membership was designed to do.
I disagree, and I think a number of practitioners of these methods would also. See
DUBOIS, D. and H. PRADE. 1990. ROUGH FUZZY SETS AND FUZZY ROUGH SETS*. International Journal of General Systems, 17(2), pp.191 - 209.

The methods for handling rough sets may look superficially like a specific case of a discontinuous fuzzy membership function, but rough and fuzzy sets were designed to deal with different kinds of uncertainty. In order to perform classification under both kinds of uncertainty, these authors developed rough fuzzy sets or fuzzy rough sets.

Their abstract says it well

"The notion of a rough set introduced by Pawlak has often been compared to that of a fuzzy set, sometimes with a view to prove that one is more general, or, more useful than the other. In this paper we argue that both notions aim to different purposes. Seen this way, it is more natural to try to combine the two models of uncertainty (vagueness and coarseness) rather than to have them compete on the same problems. First, one may think of deriving the upper and lower approximations of a fuzzy set, when a reference scale is coarsened by means of an equivalence relation. We then come close to Caianiello's C-calculus. Shafer's concept of coarsened belief functions also belongs to the same line of thought. Another idea is to turn the equivalence relation into a fuzzy similarity relation, for the modeling of coarseness, as already proposed by Farinas del Cerro and Prade. Instead of using a similarity relation, we can start with fuzzy granules which make a fuzzy partition of the reference scale. The main contribution of the paper is to clarify the difference between fuzzy sets and rough sets, and unify several independent works which deal with similar ideas in different settings or notations."

According to Google Scholar, this paper has been cited 734 times, so I'd say quite a few folks found this view worthwhile.


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