Flattening and Saturation: Two Representation Changes for Generalization
Machine Learning - Special issue on evaluating and changing representation
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Rough Problem Settings for Inductive Logic Programming
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
The Generic Rough Set Inductive Logic Programming Model and Motifs in Strings
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
A framework for reasoning with rough sets
Transactions on Rough Sets IV
Learning First-Order Rules: A Rough Set Approach
Fundamenta Informaticae - International Conference on Soft Computing and Distributed Processing (SCDP'2002)
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We investigate a Rough Set approach to treating imperfect data in Inductive Logic Programming. Due to the generality of the language, we base our approach on neighborhood systems. A first-order decision system is introduced and a greedy algorithm for finding a set of rules (or clauses) is given. Furthermore, we describe two problems for which it can be used.