Title :
Overfitting: a fuzzy neural net solution
Author :
Feuring, Thomas ; Buckley, James J. ; Hayashi, Yoichi
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Siegen Univ., Germany
Abstract :
Given most continuous h:[a,b]/spl rarr/R and /spl epsiv/>0, we show how to obtain a neural net which will approximate h, to within /spl epsiv/, uniformly over [a,b]. To construct this neural net, we first train a fuzzy neural net on a finite training set, and the needed neural net is the defuzzified trained fuzzy neural net.
Keywords :
function approximation; fuzzy neural nets; fuzzy set theory; generalisation (artificial intelligence); learning (artificial intelligence); function approximation; fuzzy neural networks; fuzzy set theory; generalisation; learning; overfitting; Computer science; Fuzzy neural networks; Fuzzy sets; Mathematics; Neural networks; Testing;
Conference_Titel :
Fuzzy Systems Conference Proceedings, 1999. FUZZ-IEEE '99. 1999 IEEE International
Conference_Location :
Seoul, South Korea
Print_ISBN :
0-7803-5406-0
DOI :
10.1109/FUZZY.1999.793207