Title :
The key theorem of learning theory based on the rough fuzzy samples
Author :
Wang, Xiao-li ; Tian, Da-Zeng ; Huang, Shu
Author_Institution :
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding, China
Abstract :
Firstly, the Khinchine law of large numbers based on the rough fuzzy samples is given. Secondly, based on the rough fuzzy samples, some concepts such as rough fuzzy expected risk functional, rough fuzzy empirical risk functional and rough fuzzy empirical risk minimization principle are proposed. Finally, the key theorem of learning theory based on the rough fuzzy sample is proved.
Keywords :
fuzzy set theory; learning (artificial intelligence); rough set theory; statistical analysis; Khinchine law; learning theory; rough fuzzy samples; Chromium; Convergence; Cybernetics; Radio frequency; Risk management; Statistical learning; Empirical risk functional; Empirical risk minimization principle; Expected risk functional; Rough fuzzy variable; The key theorem;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5581044
