DocumentCode
2897661
Title
Structural Risk Minimization Principle on Credibility Space
Author
Bai, Yun-Chao ; Ha, Ming-Hu ; Li, Jun-Hua
Author_Institution
Coll. of Econ. Sci., Hebei Univ., Baoding
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
3643
Lastpage
3649
Abstract
In this paper, the idea of the structural risk minimization (SRM) on credibility space is presented; two theorems are proven to answer two questions: is the structural risk minimization principle consistent on credibility space? (Does the risk for the functions chosen according to this principle converge to the smallest possible risk for the set S with increasing amount of observations?) What is the bound on the (asymptotic) rate of convergence?
Keywords
convergence; learning (artificial intelligence); minimisation; risk analysis; set theory; theorem proving; SRM; asymptotic convergence rate; credibility space; set theory; structural risk minimization principle; theorem proving; Chromium; Computer science; Convergence; Cybernetics; Distribution functions; Educational institutions; Fuzzy sets; Machine learning; Mathematics; Power generation economics; Risk management; Virtual colonoscopy; Credibility measure; the bounds on the rate of uniform convergence; the structural risk minimization principle;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.258586
Filename
4028703
Link To Document