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...

Full description

Bibliographic Details

Published in:	Journal of chemometrics Vol. 26; no. 7; pp. 353 - 360
Main Authors:	Xin, Ni, Gu, Xiaofeng, Wu, Hao, Hu, Yuzhu, Yang, Zhonglin
Format:	Journal Article
Language:	English
Published:	Chichester, UK John Wiley & Sons, Ltd 01.07.2012 Wiley Subscription Services, Inc
Subjects:	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 Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!