DocumentCode
424148
Title
The bounds on the rate of convergence of learning process about fuzzy examples
Author
Ha, Ming-Hu ; Tian, Jing ; Jun-hua Liu ; Wang, Xi-Zhao
Author_Institution
Coll. of Math. & Comput. Sci., Hebei Univ., Baoding, China
Volume
3
fYear
2004
fDate
26-29 Aug. 2004
Firstpage
1908
Abstract
Statistical learning theory, a recently developed new theory for pattern recognition, is a small sample statistics proposed by Vapnik et al, which deals mainly with the statistical principles when the samples are limited. The bounds on the rate of convergence play an important role in the statistical learning theory. We discuss the bounds on the risk for loss function about fuzzy examples and then estimate the rate of convergence.
Keywords
convergence; estimation theory; fuzzy set theory; learning (artificial intelligence); pattern recognition; sampling methods; convergence rate estimation; fuzzy examples; fuzzy set theory; learning process; loss function; pattern recognition; sampling method; statistical learning theory; statistical principles; Convergence; Cybernetics; Educational institutions; Fuzzy sets; Machine learning; Pattern recognition; Random variables; Risk management; Statistical learning; Statistics;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Print_ISBN
0-7803-8403-2
Type
conf
DOI
10.1109/ICMLC.2004.1382090
Filename
1382090
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