Finding relevant attributes and membership functions

作者: Tzung-Pei Hong , Jyh-Bin Chen

DOI: 10.1016/S0165-0114(97)00187-5

关键词:

摘要: Fuzzy systems that automatically derive fuzzy if-then rules from numeric data have been developed. Most to predefine membership functions in order learn. Hong and Lee proposed a general learning method derives set of given training examples using decision table. All available attributes were included the table initial for each attribute built according predefined smallest unit. Although Lee's accurately final functions, are complex if there many or unit is small. We improve by first selecting relevant building appropriate functions. These then used Experimental results on Iris show effectively induces rules.

参考文章(22)
Fuzzy logic controller IET Digital Library. pp. 199- 250 ,(1994) , 10.1049/PBPO091E_CH7
Edward Hance Shortliffe, Bruce G. Buchanan, Rule-based expert systems : the MYCIN experiments of the Stanford Heuristic Programming Project Addison-Wesley. ,(1985)
Hans Jürgen Zimmermann, Fuzzy sets, decision making, and expert systems ,(1987)
K. A. Horn, P. J. Compton, L. Lazarus, J. R. Quinlan, Inductive knowledge acquisition: a case study Proceedings of the Second Australian Conference on Applications of expert systems. pp. 137- 156 ,(1987)
J. G. Carbonell, T. M. Mitchell, R. S. Michalski, Machine Learning: An Artificial Intelligence Approach Springer Publishing Company, Incorporated. ,(2013)
D.G. Burkhardt, P.P. Bonissone, Automated fuzzy knowledge base generation and tuning [1992 Proceedings] IEEE International Conference on Fuzzy Systems. pp. 179- 188 ,(1992) , 10.1109/FUZZY.1992.258615
William Mendenhall, Robert J. Beaver, James E. Reinmuth, Statistics for management and economics ,(1971)
R. A. FISHER, THE USE OF MULTIPLE MEASUREMENTS IN TAXONOMIC PROBLEMS Annals of Human Genetics. ,vol. 7, pp. 179- 188 ,(1936) , 10.1111/J.1469-1809.1936.TB02137.X