Abstract
We introduce a technique to compute new summary information estimations (information and entropy) for fuzzy sets. Special features for these estimations are investigated. We give an algorithm for determine various information measures for fuzzy sets and fuzzy decision trees. Finally, we are using our estimations for induction of fuzzy decision trees from a group of training examples.
This investigation has been supported by the grant 01M-122 of Fund of Fundamental Researches and grant of Ministry of Education (Republic of Belarus).
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.
Similar content being viewed by others
References
Cover, T.M.: Elements of Information Theory, Wiley, New York, 1991.
Cheushev, V., Shmerko, V., Simovici, D., Yanushkevich, S.: Functional Entropy & Decision Trees. Proc. of the 28th IEEE Int.Symp. on Multiple Valued Logic, Japan, 257–262, (1998)
Safavian, S.R., Landgrebe, D.: A Survey of Decision Tree Classifier Methodology, IEEE Trans.Sys.Man Cybernet. 21, pp. 660–674, 1991.
Weber, R.: Fuzzy-ID3: a Class of Methods for Automatic Knowledge Acquisition, Proc. of the 2nd Int..Conf. on Fuzzy Logic and Neural Networks, Iizuka, Japan, pp. 265–268, 1992.
Zeidler, J., Schlosser, M.: Fuzzy Handling of Continous-Valued Attributes in Decision Trees. Proc. of MLNet Familiarization Workshop: Statistics, Machine Learning and Knowledge Discovery in Databases, Heraklion, Greece, pp. 41–46, 1995.
Kosko, B.: Neural Networks and Fuzzy Systems. Prentice-Hall, Englewood Cliffs, NJ, 1992.
Cios, K.J., Sztandera, L.M.: Continuous ID3 Algorithm with Fuzzy Entropy Measures, Proc. of the IEEE Int. Conf. on Fuzzy Systems, San Diego, CA, pp. 469–476, 1992.
Yuan, Y., Shaw, M.J.: Induction of Fuzzy Decision Trees, Fuzzy Sets and Systems, 69, pp. 125–139, 1995.
Wang, X., Chen, B., Qian, G., Ye, F.: On the Optimization of Fuzzy Decision Trees, Fuzzy Sets and Systems, 112, pp. 117–125, 2000.
Chang, R.L.P., Pavliddis, T.: Fuzzy Decision Tree Algorithms, IEEE Trans. on Systems, Man and Cybernetics, 7, pp. 28–35, 1977.
Levashenko, V., Morozevich, A., Zaitseva, E. and Kovalik, S.: Using Information Theoretical Approach for Construction of Fuzzy Decision Trees, Proc. of the 6th Int.Conf. on Information Networks, Systems and Technologies, Minsk, Belarus, pp. 164–170, 2001.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Levashenko, V.G., Zaitseva, E.N. (2002). Usage of New Information Estimations for Induction of Fuzzy Decision Trees. In: Yin, H., Allinson, N., Freeman, R., Keane, J., Hubbard, S. (eds) Intelligent Data Engineering and Automated Learning — IDEAL 2002. IDEAL 2002. Lecture Notes in Computer Science, vol 2412. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45675-9_74
Download citation
DOI: https://doi.org/10.1007/3-540-45675-9_74
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44025-3
Online ISBN: 978-3-540-45675-9
eBook Packages: Springer Book Archive