Discriminant analysis is an inappropriate method of authentication

Rodionova, Oxana Ye.; Титова, А. В.; Pomerantsev, Alexey L.

doi:10.1016/j.trac.2016.01.010

Cited by 194 publications

(80 citation statements)

References 30 publications

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“…Finally, we can repeat our notion presented in Rodionova et al “The “best” classification method does not exist. Every task at hand requires an application of a pertinent chemometric method best suited to answer the posed question.”…”

Section: Discussionsupporting

confidence: 59%

“…In our paper, we criticized the PLS‐DA method for wrong interpretation of new objects. The main drawback of this approach is its inability of proper classification of the samples, which do not belong to any of the predefined classes.…”

Section: Soft Pls‐damentioning

confidence: 99%

“…Various explanations of this consideration can be found in numerous publications. Contributing to this discussion, we have to make an important remark that, in general, this is not a fair comparison, because SIMCA and PLS‐DA have absolutely different goals and ways of modeling . SIMCA is a one‐class classifier that produces a description of a target class of objects and then detects whether a new object resembles this class or not.…”

Section: Pls‐da and Simcamentioning

confidence: 99%

“…The last issue that is presented in this paper is of methodological nature. In Rodionova et al, we discuss that PLS‐DA is an inappropriate method of authentication. In fact, PLS‐DA is a good method when used according to its intended purpose, which is discrimination.…”

Section: Introductionmentioning

confidence: 98%

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Multiclass partial least squares discriminant analysis: Taking the right way—A critical tutorial

Pomerantsev

Rodionova

2018

Journal of Chemometrics

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Here, the theory of the multi-class partial least squares discriminant analysis (PLS-DA) is presented. A distinct feature of this theory is that it does not utilize PLS scores but is entirely based on the predicted dummy responses. It is shown that the results of the multi-class PLS-DA can be presented in a straightforward way by projecting the response matrix on the "super-score" space by means of principal component analysis. Two approaches to discrimination are considered: the hard and the soft way of allocation. Correspondingly, 2 versions of PLS-DA are presented: the conventional hard PLS-DA, and the newly introduced soft PLS-DA that seems to be a novel approach in chemometrics. The quality of classification is assessed using the figures of merit (sensitivity, specificity, and efficiency). It is shown how these characteristics are used for the selection of the model complexity. A number of practical problems are investigated, such as unbalanced sizes of classes, comparison of the discriminant and the class-modeling methods and authentication by the "one against all" strategy. The paper is illustrated by real-world and simulated examples.

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Section: Discussionsupporting

confidence: 59%

Section: Soft Pls‐damentioning

confidence: 99%

Section: Pls‐da and Simcamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

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Multiclass partial least squares discriminant analysis: Taking the right way—A critical tutorial

Pomerantsev

Rodionova

2018

Journal of Chemometrics

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“…Here, QDA outperformed LDA using the same pretreatments and number of features. This is likely due to large differences between class-covariance matrices, but further investigation would be necessary to exclude overoptimistic results due to sampling inadequacies and thus biased detection models (Oliveri and Downey, 2012;Rodionova et al, 2016).…”

Section: Discriminant Analysismentioning

confidence: 99%

Near-infrared spectroscopy for detection of hailstorm damage on olive fruit

Moscetti

Haff

Monarca

et al. 2016

Postharvest Biology and Technology

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Chemometrics for Food Quality Control and Authentication

Cocchi

2017

Encyclopedia of Analytical Chemistry

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The concern of society about food nowadays extends to the several aspects linked to food consumption encompassing nutritional value, health, safety, and quality, as well as ethics, sustainability, tradition, communication, marketing, and so on. The increased information available to the consumers, the awareness of the impact of diet on healthiness, and the issues brought by globalization of the food\ud market on one hand and the institution of the Common Market (European Union (EU) countries) and its regulations on the other hand have progressively changed the leading paradigms in food science and the essential topics for the food industry. Undoubtedly, ‘quality’ is a primary criterion to access the market. However, quality is a multifaceted concept including both aspects, the set of identifiable features of a product and accountability, trustiness linked to it. Thus, quality is usually an integrated measure of several characteristics deliberately produced (sophistication, adulteration, counterfeit, appearance, etc.) or not (purity, contamination, degradation, etc.) and also of the subjective consumer’s perception of the worth of the product (to which issues such as terroir, authenticity, origin, and production practice contribute).\ud In this context, quality control and authentication require a step beyond traditional chemical analysis and characterization, which focuses mainly on single classes of constituents/properties, moving to fingerprinting, fast, nondestructive techniques. In this perspective, the role of chemometrics is of paramount importance to efficiently extract the relevant information and by providing tailored tools that allow exploratory data analysis, graphical representation, and validation of the models during all steps of data processing as well as efficient storage, retrieval, and sharing of information

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Discriminant analysis is an inappropriate method of authentication

Cited by 194 publications

References 30 publications

Multiclass partial least squares discriminant analysis: Taking the right way—A critical tutorial

Multiclass partial least squares discriminant analysis: Taking the right way—A critical tutorial

Near-infrared spectroscopy for detection of hailstorm damage on olive fruit

Chemometrics for Food Quality Control and Authentication

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