SIMCA Modeling for Overlapping Classes: Fixed or Optimized Decision Threshold? - Université de Lille Accéder directement au contenu
Article Dans Une Revue Analytical Chemistry Année : 2018

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

Résumé

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.
Fichier non déposé

Dates et versions

hal-04457316 , version 1 (14-02-2024)

Identifiants

Citer

Raffaele Vitale, Federico Marini, Cyril Ruckebusch. SIMCA Modeling for Overlapping Classes: Fixed or Optimized Decision Threshold?. Analytical Chemistry, 2018, Analytical Chemistry, 90 (18), pp.10738-10747. ⟨10.1021/acs.analchem.8b01270⟩. ⟨hal-04457316⟩
4 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More