Rough set algorithms in classification problem
Rough set methods and applications
Introduction to Algorithms
CMAR: Accurate and Efficient Classification Based on Multiple Class-Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Covering with Reducts - A Fast Algorithm for Rule Generation
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Mining border descriptions of emerging patterns from dataset pairs
Knowledge and Information Systems
Attribute set dependence in apriori-like reduct computation
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Local reducts and jumping emerging patterns in relational databases
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
Association reducts: a framework for mining multi-attribute dependencies
ISMIS'05 Proceedings of the 15th international conference on Foundations of Intelligent Systems
Transactions on rough sets XII
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This paper demonstrates how to employ rough set framework in order to induce JEPs in transactional data. The algorithm employs local reducts in order to generate desired JEPs and additional EPs. The number of the latter is decreased by preceding reduct computation with item aggregation. The preprocessing is reduced to graph coloring and solved with efficient classical heuristics. Our approach is contrasted with JEP-Producer, the recommended method for JEP induction. Moreover, a formal apparatus for classified transactional data has been proposed.