International Journal of Approximate Reasoning
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Fuzzy preference based rough sets
Information Sciences: an International Journal
An uncertain reasoning approach with application to satellite fault detection
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 3
Rough sets for selection of molecular descriptors to predict biological activity of molecules
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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Early work on case-based reasoning (CBR) reported in the literature shows the importance of soft computing techniques applied to different stages of the classical four-step CBR life cycle. This correspondence proposes a reduction technique based on rough sets theory capable of minimizing the case memory by analyzing the contribution of each case feature. Inspired by the application of the minimum description length principle, the method uses the granularity of the original data to compute the relevance of each attribute. The rough feature weighting and selection method is applied as a preprocessing step prior to the generation of a fuzzy rule system, which is employed in the revision phase of the proposed CBR system. Experiments using real oceanographic data show that the rough sets reduction method maintains the accuracy of the employed fuzzy rules, while reducing the computational effort needed in its generation and increasing the explanatory strength of the fuzzy rules