Abstract
This chapter investigates the appropriateness of the application of fuzzy decision trees on the evaluation of company audit fees, with attention to the sensitivity of the results. With the rudiments of fuzzy decision trees in a fuzzy environment, it implies a linguistic emphasis on the concomitant analysis, allowing readability in the fuzzy decision rules constructed. Two processes for the construction of membership functions (MFs) used to define the linguistic terms characterising the linguistic variables considered allowing the impact of considering alternative MFs. The tutorial fuzzy decision tree analysis clearly allows the construction processes to be exposited.
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
Abdel-Galil, T.K., Sharkawy, R.M., Salama, M.M.A., Bartnikas, R.: Partial Discharge Pattern Classification Using the Fuzzy Decision Tree Approach. IEEE Transactions on Instrumentation and Measurement 54(6), 2258–2263 (2005)
Beynon, M.J., Peel, M.J., Tang, Y.-C.: The Application of Fuzzy Decision Tree Analysis in an Exposition of the Antecedents of Audit Fees. OMEGA - International Journal of Management Science 32(2), 231–244 (2004)
Bodenhofer, U., Hüllermeier, E., Klawonn, F., Kruse, R.: Special issue on soft computing for information mining. Soft Computing 11, 397–399 (2007)
Breiman, L.: Statistical Modeling: The Two Cultures. Statistical Science 16(3), 199–231 (2001)
Chan, P., Ezzamel, M., Gwilliam, D.: Determinants of audit fees for quoted UK companies. Journal of Business Finance and Accounting 20(6), 765–786 (1993)
Chang, R.L.P., Pavlidis, T.: Fuzzy decision tree algorithms. IEEE Transactions Systems Man and Cybernetics SMC-7(1), 28–35 (1977)
Chiang, I.-J., Shieh, M.-J., Hsu, J.Y.-J., Wong, J.-M.: Building a Medical Decision Support System for Colon Polyp Screening by using Fuzzy Classification Trees. Applied Intelligence 22, 61–75 (2005)
Dombi, J., Gera, Z.: The approximation of piecewise linear membership functions and Łukasiewicz operators. Fuzzy Sets and Systems 154, 275–286 (2005)
Duda, R.O., Hart, P.E.: Pattern classification and Scene Analysis. Wiley, New York (1973)
Grauel, A., Ludwig, L.A.: Construction of differentiable membership functions. Fuzzy Sets and Systems 101, 219–225 (1999)
Herrera, F., Herrera-Viedma, E., Martinez, L.: A fusion approach for managing multi-granularity linguistic term sets in decision making. Fuzzy Sets and Systems 114(1), 43–58 (2000)
Hu, Y.-C.: Determining membership functions and minimum fuzzy support in finding fuzzy association rules for classification problems. Knowledge-Based Systems 19, 57–66 (2006)
Ishibuchi, H., Nakashima, T., Murata, T.: Three-objective genetics-based machine learning for linguistic rule extraction. Information Sciences 136, 109–133 (2001)
Kecman, V.: Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic. MIT Press, London, UK (2001)
Kovalerchuk, B., Vityaev, E.: Data Mining in Finance: Advances in Relational and Hybrid Methods. Kluwer Academic Publishers, Dordrecht (2000)
Odéjobí, O.A., Wong, S.H.S., Beaumont, A.J.: A fuzzy decision tree-based duration model for Standard Yorùbá text-to-speech synthesis. Computer Speech and Language 21(2), 325–349 (2006)
Olaru, C., Wehenkel, L.: A complete fuzzy decision tree technique. Fuzzy Sets and Systems 138(2), 221–254 (2003)
Pal, S.K., Ghosh, A.: Soft computing data mining. Information Sciences 176, 1101–1102 (2004)
Parzen, E.: On Estimation of a probability density function mode. Annals of Mathematical Statistics 33, 1065–1076 (1962)
Roa-Sepulveda, C.A., Herrera, M., Pavez-Lazo, B., Knight, U.G., Coonick, A.H.: Economic dispatch using fuzzy decision trees. Electric Power Systems Research 66, 115–122 (2003)
Singpurwalla, N.D., Booker, J.M.: Membership Functions and Probability Measures of Fuzzy Sets. Journal of the American Statistical Association 99(467), 867–877 (2004)
Thompson, J.R., Tapia, R.A.: Nonparametric Function Estimation, Modeling, and Simulation, Society for Industrial and Applied Mathematics, Philadelphia (1990)
Wang, X., Chen, B., Qian, G., Ye, F.: On the optimization of fuzzy decision trees. Fuzzy Sets and Systems 112(1), 117–125 (2000)
Wang, X., Nauck, D.D., Spott, M., Kruse, R.: Intelligent data analysis with fuzzy decision trees. Soft Computing 11, 439–457 (2007)
Yardley, J.A., Kauffman, N.L., Clairney, T.D., Albrecht, W.D.: Supplier behaviour in the US audit market. Journal of Accounting Literature 24(2), 405–411 (1992)
Yuan, Y., Shaw, M.J.: Induction of fuzzy decision trees. Fuzzy Sets and Systems 69(2), 125–139 (1995)
Zadeh, L.A.: Fuzzy Sets. Information and Control 8(3), 338–353 (1965)
Zadeh, L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems 1, 3–28 (1978)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Beynon, M.J. (2008). The Application of Fuzzy Decision Trees in Company Audit Fee Evaluation: A Sensitivity Analysis. In: Prasad, B. (eds) Soft Computing Applications in Business. Studies in Fuzziness and Soft Computing, vol 230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79005-1_5
Download citation
DOI: https://doi.org/10.1007/978-3-540-79005-1_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-79004-4
Online ISBN: 978-3-540-79005-1
eBook Packages: EngineeringEngineering (R0)