Paper Info
Title
A Quantitative Analysis of Preclusivity vs. Similarity Based Rough Approximations
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 ([3,4]). 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.
Year
DOI
Venue
2002
10.1007/3-540-45813-1_9
Rough Sets and Current Trends in Computing
Keywords
Field
DocType
different rough approximation,relative performance,generalized rough set,rough approximations,quantitative analysis,important conclusion,low quality,preclusivity relation,similar approximation,different approximation,information system,rough set
Information system,Discrete mathematics,Computer science,Theoretical computer science,Rough set,Artificial intelligence,Dominance-based rough set approach
Conference
Volume
ISSN
ISBN
2475
0302-9743
3-540-44274-X
Citations 
PageRank 
References 
4
0.62
7
Authors
2
Name
Order
Citations
PageRank
Gianpiero Cattaneo156658.22
Davide Ciucci267253.74