Calibration Methodologies

Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: Recent advances–A review

“…This encompasses tools that involve setting up a relationship between two matrices; the predictor variables X (fingerprints), on the one hand, and the variables to be predict Y (quantitative response), on the other hand. The commonly applied multivariate calibration tools are the partial least squares regression (PLS) and orthogonal projections to latent structures [34,35], support vector machine regression (SVMR) [36], principal component regression (PCR) [35] and multiple linear regression [37].…”

Rapid Non-Contact Detection of Chemical Warfare Agents by Laser Photoacoustic Spectroscopy

“…As a result, the common mode noise should decrease. However, considering the increased complexity, size, and weight of the system on the one hand, and the fact that «linear multivariate regression may be able to correct the nonlinear deviations» [ 29 ], as confirmed by the results obtained here, this implementation does not seem to be a priority.…”

“…These results were encouraging for the application of PLS, which indeed converged with six factors, thus explaining 99.0% of the variance for X (effects) variables and 99.9% of the variance for Y (responses) variables. Convergence was assessed by the root mean square of the predicted residual sum of squares (PRESS) [ 29 ]. Figure 9 (right) shows the difference between the predicted and actual DMMP, which is rather small.…”

Introducing ATR-FTIR Spectroscopy through Analysis of Acetaminophen Drugs: Practical Lessons for Interdisciplinary and Progressive Learning for Undergraduate Students

“…Once the exploration, visualization, and differentiation steps are finished, other more powerful yet more complicated techniques can be used to classify the samples visualized by PCA. Examples of those techniques are projection to latent structures or orthogonal partial least squares (PLS), − orthogonal projection to latent structures or orthogonal partial least squares discriminant analysis (OPLS-DA), and others. − These methods could be used to try discriminating the entangled Normon and Kpharm samples. In general, such methods may, for example, return plots or misclassification/confusion matrices that indicate how many samples are properly classified or not according to certain criteria (Table ).…”