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
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;
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
DOI :
10.1109/IFCSTA.2009.116