A two-stage classification procedure for near-infrared spectra based on multi-scale vertical energy wavelet thresholding and SVM-based gradient-recursive feature elimination
- Authors
- Cho, Hyunwoo; Baek, Seung-hyun; Youn, Eunseog; Jeong, Myongkee; Taylor, Adam M.
- Issue Date
- Aug-2009
- Publisher
- Palgrave Macmillan Ltd.
- Keywords
- spectra data; classification; wavelet analysis; thresholding; support vector machines; feature selection
- Citation
- Journal of the Operational Research Society, v.60, no.8, pp.1107 - 1115
- Indexed
- SCIE
SCOPUS
- Journal Title
- Journal of the Operational Research Society
- Volume
- 60
- Number
- 8
- Start Page
- 1107
- End Page
- 1115
- URI
- https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/40996
- DOI
- 10.1057/jors.2008.179
- ISSN
- 0160-5682
- Abstract
- Near infrared (NIR) spectroscopy has been extensively used in classification problems because it is fast, reliable, cost-effective, and non-destructive. However, NIR data often have several hundred or thousand variables (wavelengths) that are highly correlated with each other. Thus, it is critical to select a few important features or wavelengths that better explain NIR data. Wavelets are popular as preprocessing tools for spectra data. Many applications perform feature selection directly, based on high-dimensional wavelet coefficients, and this can be computationally expensive. This paper proposes a two-stage scheme for the classification of NIR spectra data. In the first stage, the proposed multi-scale vertical energy thresholding procedure is used to reduce the dimension of the high-dimensional spectral data. In the second stage, a few important wavelet coefficients are selected using the proposed support vector machines gradient-recursive feature elimination. The proposed two-stage method has produced better classification performance, with higher computational efficiency, when tested on four NIR data sets. Journal of the Operational Research Society (2009) 60, 1107-1115. doi:10.1057/jors.2008.179 Published online 8 April 2009
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