Type-2 Fuzzy Decision Trees
作者： Łukasz Bartczuk , Danuta Rutkowska
DOI: 10.1007/978-3-540-69731-2_20
关键词:
摘要: This paper presents type-2 fuzzy decision trees (T2FDTs) that employ sets as values of attributes. A modified double clustering algorithm is proposed a method for generating sets. allows to create T2FDTs are easy interpret and understand. To illustrate performace the in order compare them with results obtained type-1 (T1FDTs), two benchmark data sets, available on internet, have been used.
springer.com
springerlink.com参考文章(27)
Jerry M. Mendel, Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions ,(2001)
Danuta Rutkowska, Neuro-Fuzzy Architectures and Hybrid Learning ,(2001)
R. Nowicki, D. Rutkowska, Implication-Based Neuro-Fuzzy Architectures International Journal of Applied Mathematics and Computer Science. ,vol. 10, pp. 675- 701 ,(2000)
N. Henzel, J. Łęski, A Neuro-Fuzzy System Based on Logical Interpretation of If-then Rules International Journal of Applied Mathematics and Computer Science. ,vol. 10, pp. 703- 722 ,(2000)
Andrzej Piegat, Fuzzy Modeling and Control ,(2001)
Jacek M. Zurada, Introduction to artificial neural systems ,(1992)
G. Castellano, A.M. Fanelli, C. Mencar, A double-clustering approach for interpretable granulation of data systems, man and cybernetics. ,vol. 2, pp. 483- 487 ,(2002) , 10.1109/ICSMC.2002.1173459
R. Jager, Fuzzy Logic in Control TU Delft, Delft University of Technology. ,(1995)
Ronald Yager, Ranking fuzzy subsets over the unit interval conference on decision and control. ,vol. 17, pp. 1435- 1437 ,(1978) , 10.1109/CDC.1978.268154
J.M. Adamo, Fuzzy decision trees Fuzzy Sets and Systems. ,vol. 4, pp. 207- 219 ,(1980) , 10.1016/0165-0114(80)90011-1