Abstract
Rough Set Exploration System - a set of software tools featuring a library of methods and a graphical user interface is presented. Methods, features and abilities of the implemented software are discussed and illustrated with a case study in data analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Skowron A., Polkowski L.(ed.), Rough Sets in Knowledge Discovery 1 & 2, Physica Verlag, Heidelberg, 1998
Bazan J., A Comparison of Dynamic and non-Dynamic Rough Set Methods for Extracting Laws from Decision Tables, In 1, Vol. 1, pp. 321–365
Bazan J., Approximate reasoning methods for synthesis of decision algorithms (in Polish), Ph. D. Thesis, Department of Math., Comp. Sci. and Mechanics, Warsaw University, Warsaw, 1998
Bazan J., Son H. Nguyen, Trung T. Nguyen, Skowron A. and J. Stepaniuk, Decision rules synthesis for object classification. In: E. OrElowska (ed.), Incomplete Information: Rough Set Analysis, Physica-Verlag, Heidelberg, 1998, pp. 23–57.
Blackard, J.,A., Comparison of Neural Networks and Discriminant Analysis in Predicting Forest Cover Types, Ph. D. Thesis, Department of Forest Sciences, Colorado State University. Ford Collins, Colorado, 1998.
Garey M., Johnson D., Computers and Intarctability: A Guide to the Theory of NP-completness, W.H. Freeman&Co., San Francisco, 1998, (twentieth print)
Nguyen Sinh Hoa, Data regularity analysis and applications in data mining. Ph. D. Thesis, Department of Math., Comp. Sci. and Mechanics, Warsaw University, Warsaw, 1999
Nguyen Sinh Hoa, Nguyen Hung Son, Discretization Methods in Data Mining, In 1, Vol. 1, pp. 451–482
Hoa S. Nguyen, A. Skowron and P. Synak, Discovery of data patterns with applications to decomposition and classfification problems. In 1, Vol. 2, pp. 55–97.
Nguyen Hung Son, Discretization of real value attributes. Boolean reasoning approach. Ph. D. Thesis, Department of Math., Comp. Sci. and Mechanics, Warsaw University, Warsaw, 1997
Michie D., Spiegelhalter D. J., Taylor C. C., Machine Learning, Neural and Statistical Classification, Ellis Horwood, London, 1994
Pawlak Z., Rough Sets: Theoretical Aspects of Reasoning about Data, Kluwer, Dordrecht, 1991
Rauszer C., Skowron A., The Discernibility Matrices and Functions in Information Systems, In: SElowiński R. (ed.), Intelligent Decision Support, Kluwer, Dordrecht 1992.
Wróblewski J., Covering with Reducts-A Fast Algorithm for Rule Generation, Proceeding of RSCTC'98, LNAI 1424, Springer Verlag, Berlin, 1998, pp. 402–407
Bazan J., Szczuka M., The RSES Homepage, http://alfa.mimuw.edu.pl/~rses
Ørn A., The ROSETTA Homepage, http://www.idi.ntnu.no/~aleks/rosetta
Bay, S. D., The UCI KDD Archive, http://kdd.ics.uci.edu
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bazan, J.G., Szczuka, M. (2001). RSES and RSESlib - A Collection of Tools for Rough Set Computations. In: Ziarko, W., Yao, Y. (eds) Rough Sets and Current Trends in Computing. RSCTC 2000. Lecture Notes in Computer Science(), vol 2005. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45554-X_12
Download citation
DOI: https://doi.org/10.1007/3-540-45554-X_12
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43074-2
Online ISBN: 978-3-540-45554-7
eBook Packages: Springer Book Archive