Consecutive Optimization of Decision Trees Concerning Various Complexity Measures

• Autorzy: Moshkov M.Ju. , Chikalov I.V.
• Konferencja: International Conference on Soft Computing and Distributed Processing (SCDP'2002)(June 2002, Rzeszów, Poland)
• Języki publikacji: EN

Abstrakty

EN

In the paper algorithms are considered which allow to optimize decision trees consecutively againsts relatively different criterions. For decision tables over an arbitrary infinite restricted information system [4], these algorithms have polynomial time complexity.

Słowa kluczowe

EN

decision tree; complexity measures; optimization

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2004
• Tom: Vol. 61, nr 2
• Strony: 87--96
• Opis fizyczny: Bibliogr. 7 poz.

Twórcy

autor

Moshkov M.Ju.

• Faculty of Computing Mathematics and Cybernetics of Nizhny Novgorod State University, 23, Gagarina Av.. Nizhny Novgorod 603950, Russia

autor

Chikalov I.V.

• Intel Labs. Russian Research Center 30, Turgenev Str., Nizhny Novgorod 603950. Russia

Bibliografia

• [1] Chikalov. I.V.; Algorithm for constructing of decision trees with minimal number of nodes. Proceedings of the Second Inteniational Conference on Rough Sets and Current Trends in Computing (Banff, Canada, October l6-19,2000), 107-111.
• [2] Chikalov, I.V.: Algorithm for constructing of decision trees with minimal average depth. Proceedings of the Eighth International Conference on Information Processing and Management of Uncertainty in Knowledge based Systems (Madrid, Spain. July 3-7, 2000), Vol. I, 376-379.
• [31 Moshkov, M.Ju., Chikalov, I.V.: On effective algorithms for constructing of decision trees. Proceedings of the Twelfth International Conference "Problems of Theoretical Cybernetics " (Nizhny Novgorod, Russia, May 17-22, 1999). Part 2, 165 (in Russian).
• [4] Moshkov, M.Ju., Chikalov, I.V.: On algorithm for constructing of decision trees with minimal depth. Fundamenta Informaticae. 41, 2000, 295-299.
• [5] Moshkov, M.Ju., Chikalov. I.V.: Sequential optimization of decision trees realatively different complexity measures., Proceedings of the Sixth International Conference "Soft Computing and Distributed Processing " (Rzeszow, Poland, June 24-25, 2002), 53-56.
• [6] Pawlak, Z.: Rough Sets - Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, Dordrecht. Boston, London, 1991.
• [7] Skowron, A., Rauszer. C: The discernibility matrices and functions in information systems, in: Intelligent Decision Support. Handbook of Applications and Advances of the Rough Set Theory (R. Slowinski, Ed.), Kluwer Academic Publishers, Dordrecht, Boston, London, 1992, 331-362