Abstract
In this paper, we propose type-2 fuzzy decision trees in application to medical diagnosis. This means that attribute values employed in the tree structures may be characterized by type-2 fuzzy sets. Three medical benchmark data sets, available on the Internet, have been used to illustrate results of diagnosis obtained by this method.
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
Adamo, J.M.: Fuzzy decision trees. Fuzzy Sets and Systems 4, 207–219 (1980)
Bartczuk, Ł., Rutkowska, D.: A new version of the fuzzy-ID3 algorithm. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds.) ICAISC 2006. LNCS (LNAI), vol. 4029, pp. 1060–1070. Springer, Heidelberg (2006)
Bartczuk, Ł., Rutkowska, D.: Fuzzy decision trees of type-2. In: Some Aspects of Computer Science. EXIT Academic Publishing House, Warsaw (2007) (in Polish)
Blake, C., Keogh, E., Merz, C.: UCI repository of machine learning databases. University of California, Dept. of Computer Science, Irvine, CA (1998), http://www.ics.uci.edu/~mlearn/MLRepository.html
Canfora, G., Troiano, L.: Fuzzy ordering of fuzzy numbers. In: Proc. Fuzz-IEEE, Budapest, pp. 669–674 (2004)
Chang, W.: Ranking of fuzzy utilities with triangular membership functions. In: Proc. Intern. Conference on Policy Analysis and Systems, pp. 263–272 (1981)
Dong, M.: Look-ahead based fuzzy decision tree induction. IEEE Trans. Fuzzy Systems 9(3), 461–468 (2001)
Dubois, D., Prade, H.: Fuzzy Sets and Systems: Theory and Applications. Academic Press, San Diego (1980)
Hwang, C., Rhee, F.: Uncertain fuzzy clustering: interval type-2 fuzzy approach to C-means. IEEE Trans. Fuzzy Systems 15(1), 107–120 (2007)
Rhee, F.: Uncertain Fuzzy clustering: insights and recommendations. IEEE Comp. Intelligence Magazine 2(1), 44–56 (2007)
Janikow, C.Z.: Fuzzy decision trees: issues and methods. IEEE Trans. Systems Man Cybern. 28(3), 1–14 (1998)
Liang, Q., Mendel, J.M.: Interval type-2 fuzzy logic systems: theory and design. IEEE Trans. Fuzzy Systems 8, 535–550 (2000)
Mendel, J.M.: Uncertain Rule-Based Fuzzy Logic Systems - Introduction and New Directions. Prentice Hall PTR, Englewood Cliffs (2001)
Mendel, J.M.: Computing with words, when words can mean different things to different people. In: Proc. Intern. ICSC Congress on Computational Intelligence, Rochester, New York (1999)
Mendel, J.M., John, R.I.: Type-2 fuzzy sets made simple. IEEE Trans. Fuzzy Systems 10, 117–127 (2002)
Moore, R.E.: Interval Analysis. Prentice-Hall, Englewood Cliffs (1966)
Olaru, C., Wehenkel, L.: A complete fuzzy decision tree technique. Fuzzy Sets and Systems 138, 221–254 (2003)
Piegat, A.: Modeling and Fuzzy Control. EXIT Academic Publishing House, Warsaw (1999) (in Polish)
Quinlan, J.R.: Induction of decision trees. Machine Learning 1, 81–106 (1986)
Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, Inc., Los Altos (1993)
Quinlan, J.R.: Learning with continuous classes. In: Proc. 5th Australian Joint Conference on Artificial Intelligence, pp. 343–348. World Scientific, Singapore (1992)
Rutkowska, D.: Neuro-Fuzzy Architectures and Hybrid Learning. Physica-Verlag, Springer-Verlag Company, Heidelberg (2002)
Rutkowski, L.: Methods and Techniques of Artificial Intelligence. PWN, Warsaw (2005) (in Polish)
Wang, X., Borgelt, C.: Information measures in fuzzy decision trees. In: Proc. IEEE Intern. Conference on Fuzzy Systems, Budapest, vol. 1, pp. 85–90 (2004)
Yager, R.R.: Ranking fuzzy subsets over the unit interval. In: Proc. CDC, pp. 1435–1437 (1978)
Yager, R.R.: On choosing between fuzzy subsets. Kybernetes 9, 151–154 (1980)
Yager, R.R.: Procedure for ordering fuzzy sets of the unit interval. Inform. Sci. 24, 143–161 (1981)
Yuan, Y., Shaw, M.J.: Induction of fuzzy decision trees. Fuzzy Sets and Systems 69, 125–139 (1995)
Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)
Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Information Science, Part I 8, 199–249, Part II 8, 301–357, Part III 9, 43–80 (1975)
Zimmermann, H.-J.: Fuzzy Set Theory. Kluwer Academic Publishers, Boston (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Bartczuk, Ł., Rutkowska, D. (2009). Medical Diagnosis with Type-2 Fuzzy Decision Trees. In: Kącki, E., Rudnicki, M., Stempczyńska, J. (eds) Computers in Medical Activity. Advances in Intelligent and Soft Computing, vol 65. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04462-5_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-04462-5_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-04461-8
Online ISBN: 978-3-642-04462-5
eBook Packages: EngineeringEngineering (R0)