A methodology to detect outliers/inliers in prediction with PLS
- Fernández Pierna, J.A. , Jin, L. , Daszykowski, M. , Wahl, F. & Massart, D. (2003). A methodology to detect outliers/inliers in prediction with PLS. Chemom. Intell. Lab. Syst. 68: (1-2), 17-28.
| Type | Journal Article |
| Year | 2003 |
| Title | A methodology to detect outliers/inliers in prediction with PLS |
| Journal | Chemom. Intell. Lab. Syst. |
| Label | U15-0522 |
| Recnumber | 344 |
| Volume | 68 |
| Issue | 1-2 |
| Pages | 17-28 |
| Date | 28/10/2003 |
| Endnote Keywords | prediction, uncertainty, outliers|least-squares regression|cross-validation|unscrambler|error|critique|models| |
| Abstract | A study of the homogeneity of the data should be performed in order to guarantee the detection of outliers and inliers in prediction with a PLS model. For this reason, we decided to develop an automatic methodology, with a possibility for visual checking, to detect these objects. This methodology consists of three steps. First, the objects are mapped from an n-dimensional space to a 2-dimensional space using Sammon's mapping. Then, clusters in the calibration space are detected using a density-based method, and finally, the convex hull method is applied to each cluster in order to detect outliers/inliers in new samples. Several case studies were carried out with this methodology. The results obtained show that the combination of these three different techniques makes the detection of outliers and inliers for prediction easier and more accurate than classical methods. (C) 2003 Elsevier B.V. All rights reserved. |
| Notes | EnglishArticleCHEMOMETR INTELL LAB SYST728TA |
| Author address | Fernandez Pierna Juan Antonio, Quality Department of Agro-food Products, Walloon Agricultural Research Centre (CRA-W), Chaussée de Namur, 24, B-5030 Gembloux, fernandez@cra.wallonie.be |
| Fichier | |
| Caption | U15-0522-fernandez-2003.pdf |
| Authors | Fernández Pierna, J.A., Jin, L., Daszykowski, M., Wahl, F., Massart, D. |
