A new method to improve the accuracy of the near infrared models: noise addition partial least squares method
- Dardenne, P. & Fernández Pierna, J.A. (2006). A new method to improve the accuracy of the near infrared models: noise addition partial least squares method. J. Near Infrared Spectrosc. 14: (6), 349-355.
|Title||A new method to improve the accuracy of the near infrared models: noise addition partial least squares method|
|Journal||J. Near Infrared Spectrosc.|
|Endnote Keywords||NiR spectroscopy|noise addition|PLS|b coefficients||
|Abstract||The accuracy of the y vectors estimated by the NIR models depends on the quality of the reference method. In this paper the reference data values are augmented with noise. The level of noise added ranged from 0 to 20% of the variability for the mean y values. PLS models are then calculated for each addition of noise resulting in many regression coefficient vectors that are used to produce the final calibration model. This final model is selected as the one with the highest R2 with the median of all these coefficient vectors. This model applied on unchanged independent test sets produced a RMSEP that leads to a clear improvement over the original value without noise. The ability of this technique is investigated on a simulated and on an industrial data set.|
|Author address||Dardenne Pierre, Quality Department of Agro-food Products, Walloon Agricultural Research Centre (CRA-W), Chaussée de Namur, 24, B-5030 Gembloux, email@example.com|
|Authors||Dardenne, P. & Fernández Pierna, J.A.|