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» Using Rough Sets as Tools for Knowledge Discovery
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RSFDGRC
2005
Springer
134views Data Mining» more  RSFDGRC 2005»
15 years 3 months ago
The Computational Complexity of Inference Using Rough Set Flow Graphs
Pawlak recently introduced rough set flow graphs (RSFGs) as a graphical framework for reasoning from data. Each rule is associated with three coefficients, which have been shown t...
Cory J. Butz, Wen Yan, Boting Yang
FLAIRS
2003
14 years 11 months ago
Logical Identities Applied to Knowledge Discovery in Databases
Data mining is the process of extracting implicit, previously unknown, and potentially useful information from data in databases. It is widely recognized as a useful tool for deci...
James P. Buckley, Jennifer Seitzer, Yongzhi Zhang,...
URBAN
2008
128views more  URBAN 2008»
14 years 9 months ago
Discerning landslide susceptibility using rough sets
Rough set theory has been primarily known as a mathematical approach for analysis of a vague description of objects. This paper explores the use of rough set theory to manage the ...
Pece V. Gorsevski, Piotr Jankowski
ASIAMS
2007
IEEE
15 years 4 months ago
Rough-Fuzzy Granulation, Rough Entropy and Image Segmentation
This talk has two parts explaining the significance of Rough sets in granular computing in terms of rough set rules and in uncertainty handling in terms of lower and upper approxi...
Sankar K. Pal
ICCBR
2003
Springer
15 years 3 months ago
Unifying Weighting and Case Reduction Methods Based on Rough Sets to Improve Retrieval
Case-Based Reasoning systems usually retrieve cases using a similarity function based on K-NN or some derivatives. These functions are sensitive to irrelevant or noisy features. We...
Maria Salamó, Elisabet Golobardes