A threshold of ln n for approximating set cover (preliminary version)
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
A tight analysis of the greedy algorithm for set cover
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
&agr;-RST: a generalization of rough set theory
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Fast Algorithms for Mining Association Rules in Large Databases
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Discovery of Decision Rules by Matching New Objects Against Data Tables
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Approximate Reducts and Association Rules - Correspondence and Complexity Results
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
Fundamenta Informaticae
Approximation algorithms for set cover and related problems
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Ensembles of Classifiers Based on Approximate Reducts
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On Minimal Rule Sets for Almost All Binary Information Systems
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Partial Covers, Reducts and Decision Rules in Rough Sets: Theory and Applications
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Transactions on rough sets VIII
Approximate boolean reasoning: foundations and applications in data mining
Transactions on Rough Sets V
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This paper is devoted to the study of approximate algorithms for minimization of partial association rule length. It is shown that under some natural assumptions on the class NP , a greedy algorithm is close to the best polynomial approximate algorithms for solving of this NP -hard problem. The paper contains various bounds on precision of the greedy algorithm, bounds on minimal length of rules based on an information obtained during greedy algorithm work, and results of the study of association rules for the most part of binary information systems.