Similarity, interpolation, and fuzzy rule construction
Fuzzy Sets and Systems - Special issue on expert decision support systems
Axiomatics for fuzzy rough sets
Fuzzy Sets and Systems
Learning optimization in simplifying fuzzy rules
Fuzzy Sets and Systems
Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory
Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets, Fuzzy Sets and Knowledge Discovery
Rough Sets, Fuzzy Sets and Knowledge Discovery
A comparative study of fuzzy rough sets
Fuzzy Sets and Systems
IEEE Transactions on Knowledge and Data Engineering
Fuzzy Extension of Rough Sets Theory
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Information Sciences—Informatics and Computer Science: An International Journal
An axiomatic characterization of a fuzzy generalization of rough sets
Information Sciences—Informatics and Computer Science: An International Journal
Constructive and axiomatic approaches of fuzzy approximation operators
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
On fuzzy-rough sets approach to feature selection
Pattern Recognition Letters
Information-preserving hybrid data reduction based on fuzzy-rough techniques
Pattern Recognition Letters
Learning fuzzy rules from fuzzy samples based on rough set technique
Information Sciences: an International Journal
Attribute Reduction Based on Fuzzy Rough Sets
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
A new proposal for fuzzy rough approximations and gradual decision rule representation
Transactions on Rough Sets II
Information Sciences: an International Journal
On the generalization of fuzzy rough sets
IEEE Transactions on Fuzzy Systems
Attributes Reduction Using Fuzzy Rough Sets
IEEE Transactions on Fuzzy Systems
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Decision table reduction in KDD refers to the problem of selecting those input feature values that are most predictive of a given outcome by reducing a decision table like database from both vertical and horizontal directions. Fuzzy rough sets has been proven to be a useful tool of attribute reduction (i.e. reduce decision table from vertical direction). However, relatively less researches on decision table reduction using fuzzy rough sets has been performed. In this paper we focus on decision table reduction with fuzzy rough sets. First, we propose attribute-value reduction with fuzzy rough sets. The structure of the proposed value-reduction is then investigated by the approach of discernibility vector. Second, a rule covering system is described to reduce the valued-reduced decision table from horizontal direction. Finally, numerical example illustrates the proposed method of decision table reduction. The main contribution of this paper is that decision table reduction method is well combined with knowledge representation of fuzzy rough sets by fuzzy rough approximation value. The strict mathematical reasoning shows that the fuzzy rough approximation value is the reasonable criterion to keep the information invariant in the process of decision table reduction.