Principal-component analysis

{
  "id": "MLC-T-CHM-009473",
  "term": "Principal-component analysis",
  "field": "Chemistry",
  "definition": "A statistical procedure that transforms a set of possibly correlated variables into a smaller set of uncorrelated variables called principal components. This transformation identifies the directions in the data that account for the most variance, thereby reducing dimensionality while retaining most of the information. It is widely used for data visualization, noise reduction, and as a preprocessing step for other analytical methods.",
  "subject": "Analytical Chemistry",
  "see_also": [
    "factor analysis",
    "loadings",
    "non-linear iterative partial least squares",
    "principal-component factor",
    "score"
  ],
  "references": [
    "PAC, 2016, 88, 407. 'Vocabulary of concepts and terms in chemometrics (IUPAC Recommendations 2016)' on page 423 (https://doi.org/10.1515/pac-2015-0605)"
  ],
  "url": "https://mlchart.com/terminology/chemistry/principal-component-analysis/"
}