DocumentCode
511251
Title
Research on Least Squares Support Vector Machine Combinatorial Optimization Algorithm
Author
Taian, Liu ; Yunjia, Wang ; Wentong, Liu
Author_Institution
Coll. of Environ. & Spatial Inf., China Univ. of Min. & Technol. (CUMT), Xuzhou, China
Volume
1
fYear
2009
fDate
25-27 Dec. 2009
Firstpage
452
Lastpage
454
Abstract
LS-SVM(least squares support vector machine) has been widely used in engineering practice. However, the solving of LS-SVM still remains difficult under the condition of large sample. Based on algorithm of combinatorial optimization, this paper put forward the combinatorial optimization least squares support vector machine algorithm. On several different data aggregation of dimensions, the numerical value experiment and comparison are carried out on traditional LS-SVM algorithm, COLS-SVM algorithm and its improvement algorithm. The numerical value test has shown that COLS-SVM algorithm and its improvement algorithm are effective and have certain advantages on time and regression accuracy, compared with traditional LS-SVM algorithm.
Keywords
combinatorial mathematics; least squares approximations; optimisation; support vector machines; SVM; combinatorial optimization algorithm; data aggregation; least squares support vector machine; Application software; Computer applications; Educational institutions; Equations; Informatics; Least squares methods; Optimization methods; Sparse matrices; Support vector machines; Testing; Combinatorial optimization algorithm; Least squares support vector machine; Linear equations least squares support vector machine; Sparse method;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location
Chongqing
Print_ISBN
978-0-7695-3930-0
Electronic_ISBN
978-1-4244-5423-5
Type
conf
DOI
10.1109/IFCSTA.2009.116
Filename
5385037
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