Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
An Incremental Learning Algorithm for Constructing Decision Rules
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
An Algorithm for Induction of Decision Rules Consistent with the Dominance Principle
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Interpreting Low and High Order Rules: A Granular Computing Approach
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Incremental versus non-incremental rule induction for multicriteria classification
Transactions on Rough Sets II
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Based on multi-dominance discernibility matrices, an incremental algorithm INRIDDM is proposed by means of dominance-based rough set approach. For the incremental algorithm, when a new object arrives, after updating one row or one column in the matrix, we could get the updated rule sets. Computation analysis and experimental results show that the incremental algorithm INRIDDM is superior to other non-incremental algorithms on dealing with large data sets.