论文信息 - Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity Local Approach

Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity Local Approach

For problems over arbitrary information system we study the relationships among the complexity of a problem description, the minimal complexity of a decision tree solving this problem deterministically, and the minimal complexity of a decision tree solving this problem nondeterministically. We consider the local approach to investigation of decision trees where only attributes from a problem description are used for construction of decision trees solving this problem.

Mikhail Ju. Moshkov | M. Moshkov

[1] M. Yu. Moshkov,et al. On conditional tests , 1982 .

[2] Claude François Picard,et al. Théorie des questionnaires , 1965 .

[3] Z. Pawlak,et al. Rough sets perspective on data and knowledge , 2002 .

[4] Michael Ben-Or,et al. Lower bounds for algebraic computation trees , 1983, STOC.

[5] Marcin Szczuka,et al. Rough Sets in KDD , 2005 .

[6] J. Ross Quinlan,et al. Induction of Decision Trees , 1986, Machine Learning.

[7] Zdzislaw Pawlak,et al. Information systems theoretical foundations , 1981, Inf. Syst..

[8] Mikhail Ju. Moshkov,et al. Comparative Analysis of Deterministic and Nondeterministic Decision Tree Complexity , 1996, Fundam. Informaticae.

[9] Michael Ian Shamos,et al. Computational geometry: an introduction , 1985 .

[10] Andrzej Skowron,et al. The Discernibility Matrices and Functions in Information Systems , 1992, Intelligent Decision Support.

[11] E. Humby,et al. Programs from decision tables , 1973 .

[12] Janusz Zalewski,et al. Rough sets: Theoretical aspects of reasoning about data , 1996 .

[13] D. Angluin. Queries and Concept Learning , 1988 .

[14] Mikhail Ju. Moshkov. Optimization Problems for Decision Trees , 1994, Fundam. Informaticae.