Abstract
In this article, we examine the increasing use by analytical chemists of chemometric methods for treating classification problems. The methods considered are principal component analysis (PCA), canonical variates analysis (CVA), discriminant analysis (DA), and discriminant partial least squares (PLS). Overfitting, a potential hazard of multivariate modelling, is illustrated using examples of real and simulated data, and the importance of model validation is discussed.
Original language | English |
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Pages (from-to) | 216-221 |
Number of pages | 6 |
Journal | TrAC Trends in Analytical Chemistry |
Volume | 16 |
Issue number | 4 |
DOIs | |
Publication status | Published - Apr 1997 |