PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

On Minimal Inhibitory Rules for Almost All k-Valued Information Systems

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The minimal inhibitory rules for information systems can be used for construction of classifiers. We show that almost all information systems from a certain large class of information systems have relatively short minimal inhibitory rules. However, the number of such rules is not polynomial in the number of attributes and the number of objects. This class consists of all k-valued information systems, k ≥ 2, with the number of objects polynomial in the number of attributes. Hence, for efficient construction of classifiers some filtration techniques in rule generation are necessary. Another way is to work with lazy classification algorithms based on inhibitory rules.
Wydawca
Rocznik
Strony
261--272
Opis fizyczny
Bibliogr. 11 poz.
Twórcy
autor
autor
Bibliografia
  • [1] Delimata, P., Moshkov, M., Skowron, A., Suraj, Z.: Two families of classification algorithms. LNCS 4482, Springer, Heidelberg (2007) 297-304.
  • [2] Delimata, P., Moshkov, M.Ju., Skowron, A., Suraj, Z.: Inhibitory Rules in Data Analysis: A Rough Set Approach (Studies in Computational Intelligence, vol. 163). Springer, Heidelberg, 2009.
  • [3] Moshkov,M., Skowron, A., Suraj, Z.: On maximal consistent extensions of information systems. Proceedings of the Conference Decision Support Systems (Zakopane, Poland, December 2006) Vol. 1 (2007) 199-206.
  • [4] Moshkov,M., Skowron, A., Suraj, Z.: On minimal rule sets for almost all binary information systems. Fundamenta Informaticae 80(1-3) (2007) 247-258.
  • [5] Newman, D.J., Hettich, S., Blake, C.L., Merz, C.J.: UCI Repository of machine learning databases. University of California, Irvine, Department of Information and Computer Sciences (1998) http://www.ics.uci.edu/∼mlearn/MLRepository.html
  • [6] Pawlak, Z.: Rough Sets - Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht, 1991.
  • [7] Pawlak, Z.: Concurrent versus sequential - The rough sets perspective. Bulletin of the EATCS 48 (1992) 178-190.
  • [8] Pawlak, Z., Skowron, A.: Rudiments of rough sets. Information Sciences 177(1) (2007) 3-27; Rough sets: Some extensions. Information Sciences 177(1) (2007) 28-40; Rough sets and boolean reasoning. Information Sciences 177(1) (2007) 41-73.
  • [9] Skowron, A., Suraj, Z.: Rough sets and concurrency. Bulletin of the Polish Academy of Sciences 41(3) (1993) 237-254.
  • [10] Skowron, A., Suraj, Z.: Discovery of concurrent data models from experimental tables: a rough set approach. Proceedings of the First International Conference on Knowledge Discovery and Data Mining, Montreal, Canada, August 1995, AAAI Press, Menlo Park CA (1995) 288-293.
  • [11] Suraj, Z.: Some remarks on extensions and restrictions of information systems. LNAI 2005, Springer, Heidelberg (2001) 204-211.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0004-0098
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.