Regularity analysis and its applications in data mining
Rough set methods and applications
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
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
On Classifying Mappings Induced by Granular Structures
Transactions on Rough Sets IX
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
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
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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Granulation of knowledge has turned an effective tool in data classification. We propose the approach to classification of data which extends our earlier methods by considering granules of either objects or decision rules obtained either from the original training set or from its granular reflection. Members of a granule vote for the decision class of that object. We present results of tests which show that this method usually gives results at least as good as the exhaustive classifier built on rough set principles.