DocumentCode
3042841
Title
The Key Theorem of Statistical Learning Theory with Fuzzy Samples
Author
Yang, Liu ; Shicheng, Hu ; Kaikun, Dong ; Bin, Li ; Yongdong, Xu
Author_Institution
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol. at Weihai, Weihai, China
Volume
3
fYear
2009
fDate
19-21 May 2009
Firstpage
592
Lastpage
596
Abstract
The key theorem of statistical learning theory provides a theoretical basis for the applied research of support vector machine etc., so it is one of the most important theorems in learning theory. By combining fuzzy set with statistical learning theory, the key theorem of learning theory is generalized. We replace random samples with fuzzy samples. Fuzzy empirical risk minimization principle is proposed. And the key theorem of statistical learning theory with fuzzy samples is proven.
Keywords
fuzzy set theory; learning (artificial intelligence); risk analysis; support vector machines; fuzzy samples; fuzzy set theory; risk minimization principle; statistical learning; support vector machine; Computer science; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Machine learning; Random variables; Risk management; Statistical learning; Statistics; Support vector machines; SVM; fuzzy empirical risk minimization principle; fuzzy set; the key theorem;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location
Xiamen
Print_ISBN
978-0-7695-3571-5
Type
conf
DOI
10.1109/GCIS.2009.214
Filename
5209077
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