Using contrasts as data pretreatment method in pattern recognition of multivariate data

Chemometrics and Intelligent Laboratory Systems

Volumn 45, Issue 1-2, 1999, Pages 39-53

  Wu, W ^a   Guo, Q ^a   Jouan Rimbaud, D ^a   Massart, D L ^a  

^a PHARMACEUTICAL INSTITUTE   (Belgium)

Author keywords

Contrast; Data pretreatment; NIR; Partial least squares (PLS); Pattern recognition; Regularised discriminant analysis (RDA)

Indexed keywords

ANALYTIC METHOD; CHEMOMETRICS; CONFERENCE PAPER; CORRELATION FUNCTION; DATA ANALYSIS; DISCRIMINANT ANALYSIS; MATHEMATICAL ANALYSIS; METHODOLOGY; MULTIVARIATE ANALYSIS; POLLUTION; PRIORITY JOURNAL; VARIANCE;

EID: 0033580113     PISSN: 01697439     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0169-7439(98)00088-4     Document Type: Conference Paper

References (15)

1. Wu W., Walczak B., Massart D.L., Prebble K.A., Last I.R. Spectral transformation and wavelength selection in NIR spectra classification. Analytica Chimica Acta. 315:1995;243-255.
2. Barnes R.J., Dhanoa M.S., Lister S.J. Standard normal variate transformation and detrending of near-infrared diffuse reflectance spectra. Applied Spectroscopy. 43:1989;772-777.
3. Barnes R.J., Dhanoa M.S., Lister S.J. Correction to the description of standard normal variate (SNV) and de-trend (DT) transformations in practical spectroscopy with applications in food and beverage analysis (2nd edition). Journal of Near Infrared Spectroscopy. 1:1993;185-186.
4. Aucott L.S., Garthwaite P.H., Buckland S.T. Transformations to reduce the effect of particle size in near-infrared spectra. Analyst. 113:1988;1849-1854.
5. Dhanoa M.S., Lister S.J., Sanderson R., Barnes R.J. The link between multiplicative scatter correction (MSC) and standard normal variate (SNV) transformations of NIR spectra. Journal of Near Infrared Spectroscopy. 2:1994;43-47.
6. W. Wu, Q. Guo, D.L. Massart, The robust normal variate transform for pattern recognition with near-infrared data, Analytica Chimica Acta, submitted.
7. C.H. Spiegelman, Calibration: a look at the mix of theory, methods and experimental data, presented at Compana '95, Wuerzburg, Germany.
8. Friedman J.H. Regularized discriminant analysis. Journal of the American Statistical Association. 84:1989;165-175.
9. Wu W., Mallet Y., Walczak B., Penninckx W., Massart D.L., Heuerding S., Erni F. Comparison of regularized discriminant analysis, linear discriminant analysis and quadratic discriminant analysis, applied to NIR data. Analytica Chimica Acta. 329:1996;257-265.
10. Geladi P., Kowalski B.R. Partial least-squares regression: a tutorial. Analytica Chimica Acta. 185:1986;1-17.
11. Wu W., Walczak B., Massart D.L., Heuerding S., Erni F., Last I.R., Prebble K.A. Artificial neural networks in classification of NIR spectral data: design of the training set. Chemometrics and Intelligent Laboratory Systems. 33:1996;35-46.
12. J. Zupan, J. Gasteiger, Neural Networks for Chemists: An Introduction, Weinheim, New York, 1993.
13. Centner V., Massart D.L., de Noord O.E., de Jong S., Vandeginste B.M., Sterna C. Elimination of uninformative variables for multivariate calibration. Analytial Chemistry. 68:1996;3851-3858.
14. Wu W., Rutan S.C., Baldovin A., Massart D.L. Feature selection using the Kalman filter for classification of multivariate data. Analytica Chimica Acta. 335:1996;11-22.
15. Baldovin A., Wu W., Centner V., Jouan-Rimbaud D., Massart D.L., Favretto L., Turello A. Feature selection for the discrimination between pollution types with partial least squares modelling. Analyst. 121:1996;1603-1608.