In this section, we provide examples employing three models: Mamdani, Takagi Sugeno Kang, and fuzzy rule-based classification systems. So, we classify these examples into two problems which are regression and classification.

A. Regression:

   1. The four hill function:

   2. The Gas Furnace dataset [BoxJenkins1970]:

   3. The Mackey Glass dataset [MackeyGlass1977]:

B. Classification:

  1. The Iris dataset [Fisher1936]:

  2. The Pima dataset [Smith1988]: pima.5f.RData

  3. The Wine dataset [Aeberhard1992]: wine.5f.RData

4.Credit risk assessment (German datasets) [Hsieh]: german.data-numeric

 

    

The figure above illustrates the workflow on credit risk assessment used on this experiment.

 

References:

[BoxJenkins1979] Box, G. E. P., & Jenkins, G. M. "Time series analysis, forecasting and control", San Fransisco, CA: Holden Day (1970).

[MackeyGlass1977] Mackey, M., & Glass, L., "Oscillation and chaos in physiological control systems", Science, vol. 197, pp. 287 - 289 (1977).

[Fisher1936] Fisher, R.A., "The use of multiple measurements in taxonomic problems", Annual Eugenics, 7, Part II, 179 - 188 (1936); also in "Contributions to Mathematical Statistics" (John Wiley, NY, 1950).

[Smith1988] Smith, J.W., Everhart, J.E., Dickson, W.C., Knowler, W.C., and Johannes, R.S., "Using the ADAP learning algorithm to forecast the onset of diabetes mellitus", In Proceedings of the Symposium on Computer Applications and Medical Care, pp. 261--265, IEEE Computer Society Press (1988).

[Aeberhard1992] Aeberhard, S., Coomans, D., and De Vel, O.,"Comparison of Classifiers in High Dimensional Settings", Tech. Rep. no. 92-02, Dept. of Computer Science and Dept. of Mathematics and Statistics, James Cook University of North Queensland. (Also submitted to Technometrics) (1992).

[Hsieh] N. C. Hsieh, L. P. Hung, A data driven ensemble classi er for credit scoring analysis, Expert Systems with Applications 37 (1) (2010) 534-545.