Rough Sets: Mathematical Foundations
Rough Sets: Mathematical Foundations
The Paradigm of Granular Rough Computing: Foundations and Applications
COGINF '07 Proceedings of the 6th IEEE International Conference on Cognitive Informatics
On the idea of using granular rough mereological structures in classification of data
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
Rough Mereology in Classification of Data: Voting by Means of Residual Rough Inclusions
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Natural versus Granular Computing: Classifiers from Granular Structures
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Rough mereology in analysis of vagueness
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
On the idea of using granular rough mereological structures in classification of data
RSKT'08 Proceedings of the 3rd international conference on Rough sets and knowledge technology
A Logic-Algebraic Approach to Graded Inclusion
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
Granular covering selection methods dependent on the granule size
RSKT'12 Proceedings of the 7th international conference on Rough Sets and Knowledge Technology
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Granular reflections of data sets have turned out to be very effective in data classification. In this work we present results of classification of real data sets by means of an approach in which granules of objects or decision rules are built on the basis of weak variants of rough inclusions.