Variable precision rough set model
Journal of Computer and System Sciences
FUSINTER: a method for discretization of continuous attributes
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Approaches to knowledge reduction based on variable precision rough set model
Information Sciences—Informatics and Computer Science: An International Journal - Mining stream data
Exploring high-performers' required competencies
Expert Systems with Applications: An International Journal
A multicriteria decision support system for bank rating
Decision Support Systems
A Multiple-category Classification Approach with Decision-theoretic Rough Sets
Fundamenta Informaticae - Rough Sets and Knowledge Technology (RSKT 2010)
Hi-index | 12.05 |
The variable precision rough sets model (VPRS) along with many derivatives of rough set theory (RST) necessitates a number of stages towards the final classification of objects. These include, (i) the identification of subsets of condition attributes (@b-reducts in VPRS) which have the same quality of classification as the whole set, (ii) the construction of sets of decision rules associated with the reducts and (iii) the classification of the individual objects by the decision rules. The expert system exposited here offers a decision maker (DM) the opportunity to fully view each of these stages, subsequently empowering an analyst to make choices during the analysis. Its particular innovation is the ability to visually present available @b-reducts, from which the DM can make their selection, a consequence of their own reasons or expectations of the analysis undertaken. The practical analysis considered here is applied on a real world application, the credit ratings of large banks and investment companies in Europe and North America. The snapshots of the expert system presented illustrate the variation in results from the 'asymmetric' consequences of the choice of @b-reducts considered.