SIMCA Modeling for Overlapping Classes: Fixed or Optimized Decision Threshold?

An approach exploiting the principles of Receiver Operating Characteristic (ROC) curves for the simultaneous optimization of both the complexity and the decision threshold in Soft Independent Modeling of Class Analogy (SIMCA) classification models is here proposed. The outcomes resulting from the an...

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Bibliographic Details
Published in:Analytical chemistry (Washington) 2018-09, Vol.90 (18), p.10738-10747
Main Authors: Vitale, Raffaele, Marini, Federico, Ruckebusch, Cyril
Format: Article
Language:English
Subjects:
Chemical Sciences
Chemistry
Classification
Computer simulation
Decision making
Efficiency
Modelling
Optimization
or physical chemistry
Theoretical and
Validation studies
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Summary:An approach exploiting the principles of Receiver Operating Characteristic (ROC) curves for the simultaneous optimization of both the complexity and the decision threshold in Soft Independent Modeling of Class Analogy (SIMCA) classification models is here proposed. The outcomes resulting from the analysis of two simulated and four real case-studies highlight that, in the presence of strong overlap among various categories of samples, the implemented method can lead to better classification efficiency in external validation, compared to fixing such a threshold a priori. This guarantees a higher robustness toward class dispersion. On the other hand, in cases of clearer and more definite separation among the different groups of observations, their classification performance is equally satisfactory for test samples.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.8b01270