Theoretical foundations of order-based genetic algorithms
Fundamenta Informaticae - Special issue: to the memory of Prof. Helena Rasiowa
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Dynamic Reducts as a Tool for Extracting Laws from Decisions Tables
ISMIS '94 Proceedings of the 8th International Symposium on Methodologies for Intelligent Systems
RSES and RSESlib - A Collection of Tools for Rough Set Computations
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
A New Version of Rough Set Exploration System
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
Scalable Classification Method Based on Rough Sets
TSCTC '02 Proceedings of the Third International Conference on Rough Sets and Current Trends in Computing
A Study in Granular Computing: On Classifiers Induced from Granular Reflections of Data
Transactions on Rough Sets IX
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Mining Local Association Rules from Temporal Data Set
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
ICDM'11 Proceedings of the 11th international conference on Advances in data mining: applications and theoretical aspects
Using positive region to reduce the computational complexity of discernibility matrix method
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
Pairwise cores in information systems
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Combination of metric-based and rule-based classification
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part I
Approximate boolean reasoning approach to rough sets and data mining
RSFDGrC'05 Proceedings of the 10th international conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing - Volume Part II
Improving rough classifiers using concept ontology
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
The rough set exploration system
Transactions on Rough Sets III
Analogy-based reasoning in classifier construction
Transactions on Rough Sets IV
A Rough Set Approach to Multiple Classifier Systems
Fundamenta Informaticae - SPECIAL ISSUE ON CONCURRENCY SPECIFICATION AND PROGRAMMING (CS&P 2005) Ruciane-Nide, Poland, 28-30 September 2005
A View on Rough Set Concept Approximations
Fundamenta Informaticae - The 9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Conputing (RSFDGrC 2003)
Reducts and Constructs in Attribute Reduction
Fundamenta Informaticae - International Conference on Soft Computing and Distributed Processing (SCDP'2002)
Ensembles of Classifiers Based on Approximate Reducts
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P'2000)
Rough Sets and Association Rule Generation
Fundamenta Informaticae
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In a rough set approach to knowledge discovery problems, a set of rules is generated basing on training data using a notion of reduct. Because a problem of finding short reducts is NP-hard, we have to use several approximation techniques. A covering approach to the problem of generating rules based on information system is presented in this article. A new, efficient algorithm for finding local reducts for each object in data table is described, as well as its parallelization and some optimization notes. A problem of working with tolerances in our algorithm is discussed. Some experimental results generated on large data tables (concerned with real applications) are presented.