Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Relational interpretations of neighborhood operators and rough set approximation operators
Information Sciences—Informatics and Computer Science: An International Journal
Rough set approach to incomplete information systems
Information Sciences: an International Journal
&agr;-RST: a generalization of rough set theory
Information Sciences—Informatics and Computer Science: An International Journal
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A New Rough Set Approach to Multicriteria and Multiattribute Classification
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Approximate Reducts and Association Rules - Correspondence and Complexity Results
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Dominance relation and rules in an incomplete ordered information system
International Journal of Intelligent Systems
Short communication: Uncertainty measures for fuzzy relations and their applications
Applied Soft Computing
Measuring roughness of generalized rough sets induced by a covering
Fuzzy Sets and Systems
Review: Dimensionality reduction based on rough set theory: A review
Applied Soft Computing
Knowledge reduction in random information systems via Dempster-Shafer theory of evidence
Information Sciences: an International Journal
Approximation reduction in inconsistent incomplete decision tables
Knowledge-Based Systems
Attribute reduction in ordered information systems based on evidence theory
Knowledge and Information Systems
Fuzzy rough set based attribute reduction for information systems with fuzzy decisions
Knowledge-Based Systems
A vague-rough set approach for uncertain knowledge acquisition
Knowledge-Based Systems
Approximations and uncertainty measures in incomplete information systems
Information Sciences: an International Journal
A hybrid KMV model, random forests and rough set theory approach for credit rating
Knowledge-Based Systems
On interval type-2 rough fuzzy sets
Knowledge-Based Systems
Evaluation of the decision performance of the decision rule set from an ordered decision table
Knowledge-Based Systems
A novel soft set approach in selecting clustering attribute
Knowledge-Based Systems
Attribute selection based on a new conditional entropy for incomplete decision systems
Knowledge-Based Systems
Decision rule mining using classification consistency rate
Knowledge-Based Systems
A new method to determine basic probability assignment from training data
Knowledge-Based Systems
Entropy measures and granularity measures for set-valued information systems
Information Sciences: an International Journal
Rough set approach to incomplete numerical data
Information Sciences: an International Journal
Multi-granulation fuzzy rough sets
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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In order to conduct classification analysis in inconsistent ordered information systems, notions on possible and compatible distribution reductions are proposed in this paper. The judgement theorems and discernibility matrices associated with the two reductions are examined, from which we can obtain an approach to the two reductions in rough set theory. Furthermore, the dominance matrix, possible and compatible decision distribution matrices are also considered for approach to these two forms of reductions in inconsistent ordered information systems. Algorithms of matrix computation for possible and compatible distribution reductions are constructed, by which we can provide another efficient approach to these two forms of distribution reductions. To interpret and help understand the algorithm, an experimental computing program is designed and two cases are employed as case study. Results of the small-scale case are calculated and compared by the discernibility matrix and the matrix computation to verify the new method we study in this paper. The large-scale case are calculated by the experimental computing program and validated by the definition of the reductions.