C4.5: programs for machine learning
C4.5: programs for machine learning
How many queries are needed to learn?
Journal of the ACM (JACM)
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
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Concrete Mathematics: A Foundation for Computer Science
Concrete Mathematics: A Foundation for Computer Science
Machine Learning
Machine Learning
Lower bounds for algebraic computation trees
STOC '83 Proceedings of the fifteenth annual ACM symposium on Theory of computing
Approximation algorithms for set cover and related problems
Approximation algorithms for set cover and related problems
Algebraic decision trees and Euler characteristics
SFCS '92 Proceedings of the 33rd Annual Symposium on Foundations of Computer Science
Time complexity of decision trees
Transactions on Rough Sets III
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An approximate algorithm for minimization of weighted depth of decision trees is considered. A bound on accuracy of this algorithm is obtained which is unimprovable in general case. Under some natural assumptions on the class NP, the considered algorithm is close (from the point of view of accuracy) to best polynomial approximate algorithms for minimization of weighted depth of decision trees.