Improving the Classification Accuracy for Near-Infrared Spectroscopy of Chinese Salvia miltiorrhiza Using Local Variable Selection
Joint Authors
Zhu, Lianqing
Chang, Haitao
Wang, Zhongyu
Zhou, Qun
Source
Journal of Analytical Methods in Chemistry
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-29
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
In order to improve the classification accuracy of Chinese Salvia miltiorrhiza using near-infrared spectroscopy, a novel local variable selection strategy is thus proposed.
Combining the strengths of the local algorithm and interval partial least squares, the spectra data have firstly been divided into several pairs of classes in sample direction and equidistant subintervals in variable direction.
Then, a local classification model has been built, and the most proper spectral region has been selected based on the new evaluation criterion considering both classification error rate and best predictive ability under the leave-one-out cross validation scheme for each pair of classes.
Finally, each observation can be assigned to belong to the class according to the statistical analysis of classification results of the local classification model built on selected variables.
The performance of the proposed method was demonstrated through near-infrared spectra of cultivated or wild Salvia miltiorrhiza, which are collected from 8 geographical origins in 5 provinces of China.
For comparison, soft independent modelling of class analogy and partial least squares discriminant analysis methods are, respectively, employed as the classification model.
Experimental results showed that classification performance of the classification model with local variable selection was obvious better than that without variable selection.
American Psychological Association (APA)
Zhu, Lianqing& Chang, Haitao& Zhou, Qun& Wang, Zhongyu. 2018. Improving the Classification Accuracy for Near-Infrared Spectroscopy of Chinese Salvia miltiorrhiza Using Local Variable Selection. Journal of Analytical Methods in Chemistry،Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1176386
Modern Language Association (MLA)
Zhu, Lianqing…[et al.]. Improving the Classification Accuracy for Near-Infrared Spectroscopy of Chinese Salvia miltiorrhiza Using Local Variable Selection. Journal of Analytical Methods in Chemistry No. 2018 (2018), pp.1-9.
https://search.emarefa.net/detail/BIM-1176386
American Medical Association (AMA)
Zhu, Lianqing& Chang, Haitao& Zhou, Qun& Wang, Zhongyu. Improving the Classification Accuracy for Near-Infrared Spectroscopy of Chinese Salvia miltiorrhiza Using Local Variable Selection. Journal of Analytical Methods in Chemistry. 2018. Vol. 2018, no. 2018, pp.1-9.
https://search.emarefa.net/detail/BIM-1176386
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1176386