Application of genetic algorithm-support vector regression (GA-SVR) for quantitative analysis of herbal medicines

In this paper, a genetic algorithm‐support vector regression (GA‐SVR) coupled approach was proposed for investigating the relationship between fingerprints and properties of herbal medicines. GA was used to select variables so as to improve the predictive ability of the models. Two other widely used...

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Veröffentlicht in:	Journal of chemometrics Jg. 26; H. 7; S. 353 - 360
Hauptverfasser:	Xin, Ni, Gu, Xiaofeng, Wu, Hao, Hu, Yuzhu, Yang, Zhonglin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Chichester, UK John Wiley & Sons, Ltd 01.07.2012 Wiley Subscription Services, Inc
Schlagworte:	Algorithms Analytical chemistry Correlation coefficient Fingerprinting fingerprints genetic algorithm (GA) Genetic algorithms Herbal medicine herbal medicines (HM) Qualitative research Quality control Random Forests (RF) Regression analysis support vector regression (SVR)
ISSN:	0886-9383, 1099-128X
Online-Zugang:	Volltext
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