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» Rough Set Approximations in Formal Concept Analysis
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AI
1998
Springer
13 years 7 months ago
Uncertainty Measures of Rough Set Prediction
The main statistics used in rough set data analysis, the approximation quality, is of limited value when there is a choice of competing models for predicting a decision variable. ...
Ivo Düntsch, Günther Gediga
ISCI
2008
137views more  ISCI 2008»
13 years 7 months ago
Stochastic dominance-based rough set model for ordinal classification
In order to discover interesting patterns and dependencies in data, an approach based on rough set theory can be used. In particular, Dominance-based Rough Set Approach (DRSA) has...
Wojciech Kotlowski, Krzysztof Dembczynski, Salvato...
GRC
2007
IEEE
14 years 2 months ago
MGRS in Incomplete Information Systems
The original rough set model is concerned primarily with the approximation of sets described by single binary relation on the universe. In the view of granular computing, classica...
Yuhua Qian, Jiye Liang, Chuangyin Dang
EUSFLAT
2009
120views Fuzzy Logic» more  EUSFLAT 2009»
13 years 5 months ago
On M-Approximative Operators and M-Approximative Systems
Abstract-- The concept of an M-approximative system is introduced. Basic properties of the category of M-approximative systems and in a natural way defined morphisms between them a...
Alexander P. Sostak
RSKT
2009
Springer
14 years 2 months ago
Learning Optimal Parameters in Decision-Theoretic Rough Sets
A game-theoretic approach for learning optimal parameter values for probabilistic rough set regions is presented. The parameters can be used to define approximation regions in a p...
Joseph P. Herbert, Jingtao Yao