Medicine composition concentration analysis based on least square support vector machine

被引：0

作者：

Guo, XC ^{[1
]}

Chen, ZY ^{[1
]}

Teng, LR ^{[1
]}

Wu, CG ^{[1
]}

Du, TB ^{[1
]}

Lu, JH ^{[1
]}

Meng, QF ^{[1
]}

Liang, YC ^{[1
]}

机构：

[1] Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China

来源：

Proceedings of 2005 International Conference on Machine Learning and Cybernetics, Vols 1-9 | 2005年

关键词：

support vector machine; regression; absorbency;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a method of medicine composition concentration analysis based on least square support vector machines (LS-SVMs) and examines the importance of the hyperparameter choice in improvement of algorithm performance. Simulation results show that the proposed method obtains high quality precision in the generalization, compared with multiple linear regression, and that it is an efficient approach to regression estimation.

引用

页码：3704 / 3707

页数：4

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