From rough set theory to evidence theory
Advances in the Dempster-Shafer theory of evidence
A new version of the rule induction system LERS
Fundamenta Informaticae
Query approximate answering system for an incomplete DKBS
Fundamenta Informaticae - Special issue: intelligent information systems
On semantic issues connected with incomplete information databases
ACM Transactions on Database Systems (TODS)
Machine Learning
Database Mining: A Performance Perspective
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
An Algorithm for Finding Equivalence Relations from Tables with Non-Deterministic Information
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Attribute dependency functions considering data efficiency
International Journal of Approximate Reasoning
Transactions on Rough Sets II
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Rough sets theory depending upon deterministic information has recently been applied to machine learning, knowledge discovery and knowledge acquisition. For handhng some incomplete information, we are now discussing rough sets on non-deterministic information and we have developed some tool programs. In this paper, we propose a definition for dependencies of attributes on non-deterministic information and an algorithm for checking it. According to this algorithm, we have reahzed a program. To clarify the dependency on non-deterministic information will be useful for extraction of rules from nondeterministic information.