Fuzzy preference based rough sets
Information Sciences: an International Journal
An attribute reduct algorithm based on clustering
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
Application rough sets theory to ordinal scale data for discovering knowledge
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Reduction of attributes in ordinal decision systems
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
The rough set-based algorithm for two steps
ICONIP'11 Proceedings of the 18th international conference on Neural Information Processing - Volume Part II
Hi-index | 0.01 |
Rough set theory has been successfully applied in selecting attributes to improve the effectiveness in deriving decision trees/rules for decisions and classification problems. When decisions involve ordinal classes, the rough set reduction process should try to preserve the order relation generated by the decision classes. Previous works on rough sets when applied to ordinal decision systems still focus on preserving the information relating to the decision classes and not the underlying order relation. In this paper, we propose a new way of evaluating and finding reducts involving ordinal decision classes which focus on the order generated by the ordinal decision classes.