Introduction to operations research, 4th ed.
Introduction to operations research, 4th ed.
GRASP: A Search Algorithm for Propositional Satisfiability
IEEE Transactions on Computers
Mining the most interesting rules
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Outlier detection based on rough sets theory
Intelligent Data Analysis
On New Concept in Computation of Reduct in Rough Sets Theory
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
A Predictive Analysis on Medical Data Based on Outlier Detection Method Using Non-Reduct Computation
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Finding rough set reducts with SAT
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Finding rough and fuzzy-rough set reducts with SAT
Information Sciences: an International Journal
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The paper presents the Integer Programming (IP) algorithms in mining a compact rough classification model. The algorithm is based on creating a 0--1 integer programming model from a rough discernibility relations of a decision system (DS) to find minimum selection of important attributes which is called reduct in rough set theory. A branch and bound search strategy that performs a non-chronological backtracking is proposed to solve the problem. The experimental result shows that the proposed IP algorithm has significantly reduced the number of rules generated from the obtained reducts with high percentage of classification accuracy. The branch and bound search strategy has shown reduction in certain amount of search.