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
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;
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
DOI :
10.1109/GCIS.2009.214