Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Knowledge discovery by application of rough set models
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Machine Learning
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Relational Data Mining
Data Transformation and Rough Sets
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
A Rough Set Approach to Inductive Logic Programming
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
The generic rough set inductive logic programming (gRS--ILP) model
Data mining, rough sets and granular computing
Relational Data and Rough Sets
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
Satisfiability of Formulas from the Standpoint of Object Classification: The RST Approach
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
Relational Data and Rough Sets
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
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The aim of this paper is to introduce and investigate an algorithm RSRL for finding first--order logic rules. Rough set methodology is used in the process of selecting literals which may be a part of a rule. The criterion of selecting a literal is as follows: only such a literal is selected, which added to the rule makes the rule discerning the most examples which were indiscernible so far.