A rough set approach to selecting attributes for ordinal prediction

Rough set theory has been successfully applied in selecting attributes to improve the effectiveness in derivation of decision trees/rules for classification. When the classification involves ordinal classes, the rough set reduction process should take into consideration the ordering of the classes. In this paper we propose a new way of evaluating and finding reducts for ordinal classification.