Abstract
The framework for decision value oriented decomposition of data tables is stated with examples of its applications to partially generalized reasoning. Operation of synthesis of information is introduced for distributed decision tables. Theoretical foundations are built on the basis of the main factors of quality of reasoning, by referring to rough set, Dempster-Shafer and statistical theories.
This paper was supported by the State Committee for Scientific Research grant, KBN 8T11C01011.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Dempster A.P., Upper and lower probabilities induced from a multivalued mapping; Annals of Mathematical Statistics, 38, pp.325–339, 1967.
Nguyen S.H., Nguyen H.S., Skowron A., Searching for Features defined by Hyperplanes in Proceedings of the Ninth International Symposium on Methodologies for Information Systems ISMIS'96, Z.W. Rag, M. Michalewicz (eds.), June, Zakopane, Poland; Lecture Notes in AI 1079, Berlin, Springer Verlag, pp.366–375, 1996.
Nguyen S.H., Nguyen T.T., Polkowski L., Skowron A., Synak P., Wróblewski J., Decision Rules for Large Data Tables in Proceedings of Symposium on Modelling, Analysis and Simulation vol 1, Computational Engineering in Systems Applications CESA'96, July 9–12, Lille, France, pp.942–947, 1996.
Nguyen S.H., Polkowski L., Skowron A., Synak P., Wróblewski J., Searching for Approximate Description of Decision Classes in Proceedings of the Fourth International Workshop on Rough Sets, Fuzzy Sets and Machine Discovery RSFD'96, November 6–8, Tokyo, Japan; the University of Tokyo, pp. 153–161, 1996.
Pawlak Z., Rough Sets. Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, Dordrecht, 1991.
Pawlak Z., Skowron A., Rough Membership Functions; Advances in the Dempster-Shafer Theory of Evidence, Yager R.R., Fedrizzi M., Kacprzyk J.(eds.), John Wiley & Sons, New York, pp.251–271, 1994.
Payne J.W., Bettman J.R., Johnson E.J., The Adaptive Decision Maker, Cambridge University Press, 1993.
Polkowski L., Skowron A., Rough mereology: a new paradigm for approximate reasoning in International Journal of Approximate Reasoning, in print.
Shafer G., A Mathematical Theory of Evidence, Princeton University Press, 1976.
Skowron A., Synthesis of Adaptive Decision Systems from Experimental Data; Proceedings of the Fifth Scandinavian Conference on Artificial Intelligence SCAI-95, Aamodt A., Komorowski J.(eds.), Amsterdam, IOS Press, pp.220–238, 1995.
Skowron A., Grzymala-Busse J., From Rough Set Theory to Evidence Theory in Advances in the Dempster-Shafer Theory of Evidence, Yager R.R., Fedrizzi M., Kacprzyk J.(eds.), John Wiley & Sons, New York, pp.193–236, 1994.
Skowron A., Rauszer C., The Discernibility Matrices and Functions in Information Systems in Intelligent Decision Support. Handbook of Applications and Advances of the Rough Sets Theory, Slowinski R.(ed.), Kluwer, Dordrecht, pp.331–362, 1992.
Ślezak D., Approximate Reducts in Decision Tables; Proceedings of Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU 96, Granada, July 1–5, Universidad de Granada, pp.1159–1164, 1996.
Vapnik V., Estimation of Dependencies Based on Empirical Data, Springer Series in Statistics, Springer-Verlag, 1982.
Wasserman L.A., Belief Functions and Statistical Inference; The Canadian Journal of Statistics Vol.18, No.3, pp.183–196, 1990.
Wróblewski J., Finding minimal reducts using genetic algorithms in Proceedings of the Second Annual Joint Conference on Information Sciences, September 28–October 1, Wrightsville Beach, NC, pp.186–189, 1995.
Ziarko W., Variable Precision Rough Set Model; Journal of Computer and System Sciences, 40, pp.39–59, 1993.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Ślezak, D. (1997). Decision value oriented decomposition of data tables. In: Raś, Z.W., Skowron, A. (eds) Foundations of Intelligent Systems. ISMIS 1997. Lecture Notes in Computer Science, vol 1325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63614-5_47
Download citation
DOI: https://doi.org/10.1007/3-540-63614-5_47
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63614-4
Online ISBN: 978-3-540-69612-4
eBook Packages: Springer Book Archive