Rough set theory and its applications

Authors

  • Zdzisław Pawlak Institute of Theoretical and Applied Informatics image/svg+xml

DOI:

https://doi.org/10.26636/jtit.2002.140

Keywords:

rough set, decision rules, churn modeling

Abstract

In this paper rudiments of the theory will be outlined, and basic concepts of the theory will be illustrated by a simple tutorial example, concerning churn modeling in telecommunications. Real life applications require more advanced extensions of the theory but we will not discuss these extensions here. Rough set theory has an overlap with many other theories dealing with imperfect knowledge, e.g., evidence theory, fuzzy sets, Bayesian inference and others. Nevertheless, the theory can be regarded as an independent, complementary, not competing, discipline in its own rights.

Downloads

Download data is not yet available.

References

[1] J. Grant, "Churn modeling by rough set approach", manuscript, 2001.
View in Google Scholar

[2] S. K. Pal and A. Skowron, Eds., Rough Fuzzy Hybridization. Springer, 1999.
View in Google Scholar

[3] Z. Pawlak, Rough Sets - Theoretical Aspects of Reasoning about Data. Boston, London, Dordrecht: Kluwer, 1991.
View in Google Scholar

[4] Z. Pawlak, "Decision rules, Bayes' rule and rough sets", in New Direction in Rough Sets, Data Mining, and Granular-Soft Computing, N. Zhong, A. Skowron, and S. Ohsuga, Eds. Springer, 1999, pp. 1-9.
View in Google Scholar

[5] Z. Pawlak, "New look Bayes' theorem - the rough set outlook", in Proc. Int. RSTGC-2001, Matsue Shimane, Japan, May 2001, pp. 1-8; Bull. Int. Rough Set Soc., vol. 5, no. 1/2, 2001.
View in Google Scholar

[6] L. Polkowski and A. Skowron, Eds., Rough Sets and Current Trends in Computing. Lecture Notes in Artificial Intelligence 1424, Springer, 1998.
View in Google Scholar

[7] L. Polkowski and A. Skowron, Eds., Rough Sets in Knowledge Discovery. Vol. 1-2, Springer, 1998.
View in Google Scholar

[8] L. Polkowski, S. Tsumoto, and T. Y. Lin, Eds., Rough Set Methods and Applications - New Developments in Knowledge Discovery in Information Systems. Springer, 2000, to appear.
View in Google Scholar

[9] N. Zhong, A. Skowron, and S. Ohsuga, Eds., New Direction in Rough Sets, Data Mining, and Granular-Soft Computing. Springer, 1999.
View in Google Scholar

Downloads

Submitted

2023-04-07

Published

2002-09-30

Issue

No. 3 (2002)

Section

ARTICLES FROM THIS ISSUE

License

Copyright (c) 2002 Journal of Telecommunications and Information Technology

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Z. Pawlak, “Rough set theory and its applications”, JTIT, vol. 9, no. 3, pp. 7–10, Sep. 2002, doi: 10.26636/jtit.2002.140.

Most read articles by the same author(s)