Title :
The key theorem of learning theory about fuzzy examples
Author :
Ha, Minghu ; Tang, Wen-guang ; Yun-Chao Bai
Author_Institution :
Fac. of Mathematics & Comput. Sci., Hebei Univ., China
Abstract :
After the presence of the key theorem of learning theory, statistical learning theory has been formed. But the examples which it has studied are all random vectors, in theory there is no the case of fuzzy random vectors. In other words, when the characters are very difficult to distract (namely the characters are fuzzy) , we have to use fuzzy random vectors to be the examples. In this paper, we give one method to deal with this kind of problems, and give the feasibility of this method.
Keywords :
fuzzy set theory; learning (artificial intelligence); statistical analysis; FERM principle; fuzzy examples; fuzzy random vectors; fuzzy risk empirical functional; learning theory; statistical learning theory; strictly consistent convergence; Bismuth; Computer science; Convergence; Cybernetics; Fuzzy sets; Machine learning; Mathematics; Random variables; Risk management; Statistical learning;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259671