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» Approximations and Rough Sets Based on Tolerances
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RSKT
2010
Springer
13 years 7 months ago
Naive Bayesian Rough Sets
A naive Bayesian classifier is a probabilistic classifier based on Bayesian decision theory with naive independence assumptions, which is often used for ranking or constructing a...
Yiyu Yao, Bing Zhou
ISCI
2008
137views more  ISCI 2008»
13 years 8 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...
ASIAMS
2007
IEEE
14 years 2 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
AI
1998
Springer
13 years 8 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
JACIII
2006
114views more  JACIII 2006»
13 years 8 months ago
A Theoretical Formulation of Object-Oriented Rough Set Models
ata forms, and abstract structural hierarchy based on is-a relationship and has-a relationship. Object structures illustrate many kinds of objects and actual dependence among objec...
Yasuo Kudo, Tetsuya Murai