A simple idea on applying large regression coefficient to improve the genetic algorithm-PLS for variable selection in multivariate calibration

Chemometrics and Intelligent Laboratory Systems

Volumn 130, Issue , 2014, Pages 76-83

  Yun, Yong Huan ^a   Cao, Dong Sheng ^a   Tan, Min Li ^a   Yan, Jun ^a   Ren, Da Bing ^a   Xu, Qing Song ^a   Yu, Ling ^b   Liang, Yi Zeng ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b Shanghai Tobacco Group Co Ltd   (China)

Author keywords

Genetic algorithm; Multivariate calibration; Partial least squares; Regression coefficient; Variable selection

Indexed keywords

ARTICLE; CALIBRATION; CONTROLLED STUDY; GENETIC ALGORITHM; INTERMETHOD COMPARISON; MATHEMATICAL MODEL; MULTIVARIATE ANALYSIS; PARTIAL LEAST SQUARES REGRESSION; PRIORITY JOURNAL; PROCESS OPTIMIZATION; REGRESSION COEFFICIENT; SIMULATION; STATISTICAL PARAMETERS;

EID: 84887237244     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2013.09.007     Document Type: Article

References (42)

1. Kalivas J.H., Roberts N., Sutter J.M. Global optimization by simulated annealing with wavelength selection for ultraviolet-visible spectrophotometry. Anal. Chem. 1989, 61:2024-2030.
2. Spiegelman C.H., McShane M.J., Goetz M.J., Motamedi M., Yue Q.L., Coté G.L. Theoretical justification of wavelength selection in PLS calibration: development of a new algorithm. Anal. Chem. 1998, 70:35-44.
3. Xu L., Schechter I. Wavelength selection for simultaneous spectroscopic analysis. Experimental and theoretical study. Anal. Chem. 1996, 68:2392-2400.
4. Kalivas J.H. Two data sets of near infrared spectra. Chemometr. Intell. Lab. 1997, 37:255-259.
5. Jouan-Rimbaud D., Walczak B., Massart D.L., Last I.R., Prebble K.A. Comparison of multivariate methods based on latent vectors and methods based on wavelength selection for the analysis of near-infrared spectroscopic data. Anal. Chim. Acta 1995, 304:285-295.
6. Centner V., Massart D.-L., de Noord O.E., de Jong S., Vandeginste B.M., Sterna C. Elimination of uninformative variables for multivariate calibration. Anal. Chem. 1996, 68:3851-3858.
7. Cai W., Li Y., Shao X. A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra. Chemometr. Intell. Lab. 2008, 90:188-194.
8. Li H.-D., Liang Y.-Z., Xu Q.-S., Cao D.-S. Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration. Anal. Chim. Acta 2009, 648:77-84.
9. Zheng K., Li Q., Wang J., Geng J., Cao P., Sui T., Wang X., Du Y. Stability competitive adaptive reweighted sampling (SCARS) and its applications to multivariate calibration of NIR spectra. Chemometr. Intell. Lab. 2012, 112:48-54.
10. Shao X., Du G., Jing M., Cai W. Application of latent projective graph in variable selection for near infrared spectral analysis. Chemom. Intell. Lab. Syst. 2012, 114:44-49.
11. Shao X., Zhang M., Cai W. Multivariate calibration of near-infrared spectra by using influential variables. Anal. Methods 2012, 4:467.
12. Araújo M.C.U., Saldanha T.C.B., Galvão R.K.H., Yoneyama T., Chame H.C., Visani V. The successive projections algorithm for variable selection in spectroscopic multicomponent analysis. Chemometr. Intell. Lab. 2001, 57:65-73.
13. Li H.-D., Xu Q.-S., Liang Y.-Z. Random frog: an efficient reversible jump Markov Chain Monte Carlo-like approach for variable selection with applications to gene selection and disease classification. Anal. Chim. Acta 2012, 740:20-26.
14. Yun Y.-H., Li H.-D., Wood L.R.E., Fan W., Wang J.-J., Cao D.-S., Xu Q.-S., Liang Y.-Z. An efficient method of wavelength interval selection based on random frog for multivariate spectral calibration. Spectrochim. Acta. A 2013, 111:31-36.
15. Martens H., Naes T. Multivariate Calibration 1989, Wiley, New York.
16. Blanchet F.G., Legendre P., Borcard D. Forward selection of explanatory variables. Ecology 2008, 89:2623-2632.
17. Sutter J.M., Kalivas J.H. Comparison of forward selection, backward elimination, and generalized simulated annealing for variable selection. Microchem. J. 1993, 47:60-66.
18. Arakawa M., Yamashita Y., Funatsu K. Genetic algorithm-based wavelength selection method for spectral calibration. J. Chemometr. 2011, 25:10-19.
19. Bangalore A.S., Shaffer R.E., Small G.W., Arnold M.A. Genetic algorithm-based method for selecting wavelengths and model size for use with partial least-squares regression: application to near-infrared spectroscopy. Anal. Chem. 1996, 68:4200-4212.
20. Lucasius C.B., Beckers M.L.M., Kateman G. Genetic algorithms in wavelength selection: a comparative study. Anal. Chim. Acta 1994, 286:135-153.
21. Yang J., Honavar V. Feature subset selection using a genetic algorithm. IEEE Intell. Syst. 1998, 13:44-49.
22. Mehmood T., Liland K.H., Snipen L., Sæbø S. A review of variable selection methods in Partial Least Squares Regression. Chemometr. Intell. Lab. 2012, 118:62-69.
23. Zou X., Zhao J., Povey M.J.W., Holmes M., Mao H. Variables selection methods in near-infrared spectroscopy. Anal. Chim. Acta 2010, 667:14-32.
24. Holland J. Adaptation in Natural and Artificial Systems 1975, The University of Michigan Press, Michigan.
25. Leardi R. Genetic algorithms in chemometrics and chemistry: a review. J. Chemom. 2001, 15:559-569.
26. Niazi A., Leardi R. Genetic algorithms in chemometrics. J. Chemom. 2012, 26:345-351.
27. Jouan-Rimbaud D., Massart D.-L., Leardi R., De Noord O.E. Genetic algorithms as a tool for wavelength selection in multivariate calibration. Anal. Chem. 1995, 67:4295-4301.
28. Leardi R. Application of genetic algorithm-PLS for feature selection in spectral data sets. J. Chemom. 2000, 14:643-655.
29. Leardi R., Lupiáñez González A. Genetic algorithms applied to feature selection in PLS regression: how and when to use them. Chemometr. Intell. Lab. 1998, 41:195-207.
30. Broadhurst D., Goodacre R., Jones A., Rowland J.J., Kell D.B. Genetic algorithms as a method for variable selection in multiple linear regression and partial least squares regression, with applications to pyrolysis mass spectrometry. Anal. Chim. Acta 1997, 348:71-86.
31. Arcos M.J., Alonso C., Cruz Ortiz M. Genetic-algorithm-based potential selection in multivariant voltammetric determination of indomethacin and acemethacin by partial least squares. Electrochim. Acta 1997, 43:479-485.
32. Ding Q., Small G.W., Arnold M.A. Genetic Algorithm-based wavelength selection for the near-infrared determination of glucose in biological matrixes: initialization strategies and effects of spectral resolution. Anal. Chem. 1998, 70:4472-4479.
33. Depczynski U., Frost V.J., Molt K. Genetic algorithms applied to the selection of factors in principal component regression. Anal. Chim. Acta 2000, 420:217-227.
34. Lin L., Ustin L., Riano D. Retrieval of fresh leaf fuel moisture content using genetic algorithm partial least squares (GA-PLS) modeling. IEEE Geosci. Remote. Sens. 2007, 4:216-220.
35. Roger J.M., Bellon-Maurel V. Using genetic algorithms to select wavelengths in near-infrared spectra: application to sugar content prediction in cherries. Appl. Spectrosc. 2000, 54:1313-1320.
36. Sagrado S., Cronin M.T.D. Application of the modelling power approach to variable subset selection for GA-PLS QSAR models. Anal. Chim. Acta 2008, 609:169-174.
37. Riahi S., Ganjali M.R., Norouzi P., Jafari F. Application of GA-MLR, GA-PLS and the DFT quantum mechanical (QM) calculations for the prediction of the selectivity coefficients of a histamine-selective electrode. Sensors Actuators B Chem. 2008, 132:13-19.
38. Li R.F., Wang X.Z., Abebe S.B. Monitoring batch cooling crystallization using NIR: development of calibration models using genetic algorithm and PLS. Part. Part. Syst. Charact. 2008, 25:314-327.
39. Leardi R., Boggia R., Terrile M. Genetic algorithms as a strategy for feature selection. J. Chemom. 1992, 6:267-281.
40. Frenich A.G., Jouan-Rimbaud D., Massart D.L., Kuttatharmmakul S., Galera M.M., Vidal J.L.M. Wavelength selection method for multicomponent spectrophotometric determinations using partial least squares. Analyst 1995, 120:2787-2792.
41. Forina M., Drava G., Armanino C., Boggia R., Lanteri S., Leardi R., Corti P., Conti P., Giangiacomo R., Galliena C., Bigoni R., Quartari I., Serra C., Ferri D., Leoni O., Lazzeri L. Transfer of calibration function in near-infrared spectroscopy. Chemometr. Intell. Lab. 1995, 27:189-203.
42. Pizarro Millán C., Forina M., Casolino C., Leardi R. Extraction of representative subsets by potential functions method and genetic algorithms. Chemometr. Intell. Lab. 1998, 40:33-52.