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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Vydáno v:	Journal of chemometrics Ročník 26; číslo 7; s. 353 - 360
Hlavní autoři:	Xin, Ni, Gu, Xiaofeng, Wu, Hao, Hu, Yuzhu, Yang, Zhonglin
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Chichester, UK John Wiley & Sons, Ltd 01.07.2012 Wiley Subscription Services, Inc
Témata:	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
On-line přístup:	Získat plný text
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