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פותח על ידי קלירמאש פתרונות בע"מ -
Ridge regression for NIR analysis with multicollinearity
Year:
2001
Source of publication :
Acta Horticulturae
Authors :
פליק, אלעזר
;
.
פסטרנק, חנוך
;
.
שמילוביץ', זאב
;
.
Volume :
562
Co-Authors:
Pasternak, H., Inst. of Agricultural Engineering, A.R.O., Volcani Center, Bet Dagan 50250, Israel
Schmilovitch, Z., Inst. of Agricultural Engineering, A.R.O., Volcani Center, Bet Dagan 50250, Israel
Fallik, E., Inst. of Agricultural Engineering, A.R.O., Volcani Center, Bet Dagan 50250, Israel
Edan, Y., Dept. of Industrial Engineering and Managemnt, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel
Facilitators :
From page:
265
To page:
268
(
Total pages:
4
)
Abstract:
High intercorrelation between absorbances at different wavelengths is common in near infrared (NIR) analysis. NIR reflectance analysis was conducted to predict carotene in fresh tomatoes. When linear regression is employed the estimated parameters are practically random numbers, however high correlations are obtained between the predicted and true values (R=0.78). Ridge regression yields estimators with normal values, with lower parameter correlations (R=0.74). However, ridge regression is capable of overcoming noise versus linear regression which is not capable of predicting carotene in the presence of minor noise and multicollinearity.
Note:
Related Files :
Lycopersicon esculentum
Multicollinearity
near infrared spectroscopy
Ridge regression
Solanum lycopersicum
spectroscopy
tomato
עוד תגיות
תוכן קשור
More details
DOI :
Article number:
0
Affiliations:
Database:
סקופוס
Publication Type:
מאמר מתוך כינוס
;
.
Language:
אנגלית
Editors' remarks:
ID:
26300
Last updated date:
02/03/2022 17:27
Creation date:
17/04/2018 00:21
Scientific Publication
Ridge regression for NIR analysis with multicollinearity
562
Pasternak, H., Inst. of Agricultural Engineering, A.R.O., Volcani Center, Bet Dagan 50250, Israel
Schmilovitch, Z., Inst. of Agricultural Engineering, A.R.O., Volcani Center, Bet Dagan 50250, Israel
Fallik, E., Inst. of Agricultural Engineering, A.R.O., Volcani Center, Bet Dagan 50250, Israel
Edan, Y., Dept. of Industrial Engineering and Managemnt, Ben-Gurion University of the Negev, Beer Sheva 84105, Israel
Ridge regression for NIR analysis with multicollinearity
High intercorrelation between absorbances at different wavelengths is common in near infrared (NIR) analysis. NIR reflectance analysis was conducted to predict carotene in fresh tomatoes. When linear regression is employed the estimated parameters are practically random numbers, however high correlations are obtained between the predicted and true values (R=0.78). Ridge regression yields estimators with normal values, with lower parameter correlations (R=0.74). However, ridge regression is capable of overcoming noise versus linear regression which is not capable of predicting carotene in the presence of minor noise and multicollinearity.
Scientific Publication
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