Soft independent modelling of class analogy

{
  "id": "MLC-T-CHM-010968",
  "term": "Soft independent modelling of class analogy",
  "field": "Chemistry",
  "definition": "A supervised classification method in chemometrics that builds a separate principal component analysis (PCA) model for each predefined class of samples. To classify a new, unknown sample, its data is fitted to each class model, and the residual variance is calculated. The sample is assigned to the class for which its distance to the model is smallest, provided it falls within a statistical limit; otherwise, it is classified as an outlier.",
  "subject": "Analytical Chemistry",
  "see_also": [
    "supervised classification",
    "disjoint principal component analysis",
    "principal-component analysis",
    "principal-component factor"
  ],
  "references": [
    "PAC, 2016, 88, 407. 'Vocabulary of concepts and terms in chemometrics (IUPAC Recommendations 2016)' on page 432 (https://doi.org/10.1515/pac-2015-0605)"
  ],
  "url": "https://mlchart.com/terminology/chemistry/soft-independent-modelling-of-class-analogy/"
}