Document Detail

A consensus least squares support vector regression (LS-SVR) for analysis of near-infrared spectra of plant samples.
MedLine Citation:
PMID:  19071605     Owner:  NLM     Status:  In-Data-Review    
Consensus modeling of combining the results of multiple independent models to produce a single prediction avoids the instability of single model. Based on the principle of consensus modeling, a consensus least squares support vector regression (LS-SVR) method for calibrating the near-infrared (NIR) spectra was proposed. In the proposed approach, NIR spectra of plant samples were firstly preprocessed using discrete wavelet transform (DWT) for filtering the spectral background and noise, then, consensus LS-SVR technique was used for building the calibration model. With an optimization of the parameters involved in the modeling, a satisfied model was achieved for predicting the content of reducing sugar in plant samples. The predicted results show that consensus LS-SVR model is more robust and reliable than the conventional partial least squares (PLS) and LS-SVR methods.
Yankun Li; Xueguang Shao; Wensheng Cai
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Publication Detail:
Type:  Journal Article     Date:  2006-11-20
Journal Detail:
Title:  Talanta     Volume:  72     ISSN:  1873-3573     ISO Abbreviation:  Talanta     Publication Date:  2007 Apr 
Date Detail:
Created Date:  2008-12-16     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  2984816R     Medline TA:  Talanta     Country:  England    
Other Details:
Languages:  eng     Pagination:  217-22     Citation Subset:  -    
Department of Chemistry, Nankai University, Tianjin 300071, PR China.
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