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
Rules in incomplete information systems
Information Sciences: an International Journal
&agr;-RST: a generalization of rough set theory
Information Sciences—Informatics and Computer Science: An International Journal
Various approaches to reasoning with frequency based decision reducts: a survey
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
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
Normalized Decision Functions and Measures for Inconsistent Decision Tables Analysis
Fundamenta Informaticae
Ensembles of Classifiers Based on Approximate Reducts
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P'2000)
On Construction of Partial Reducts and Irreducible Partial Decision Rules
Fundamenta Informaticae - New Frontiers in Scientific Discovery - Commemorating the Life and Work of Zdzislaw Pawlak
Universal Attribute Reduction Problem
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Approximation algorithms for combinatorial problems
Journal of Computer and System Sciences
On partial covers, reducts and decision rules with weights
Transactions on rough sets VI
On partial covers, reducts and decision rules
Transactions on rough sets VIII
Approximate boolean reasoning: foundations and applications in data mining
Transactions on Rough Sets V
Hi-index | 0.00 |
In the paper, some generalizations of the notions of reduct, test (superreduct), partial (approximate) reduct and partial test are considered. The accuracy of greedy algorithm for construction of partial test is investigated. A lower bound on the minimal cardinality of partial reducts based on an information about greedy algorithm work is studied. A bound on the precision of greedy algorithm which does not depend on the number of pairs of rows of a decision table which should be separated is obtained. Results of experiments with greedy algorithm are discussed.