Concept information
Término preferido
principal component analysis
Definición
- Principal component analysis (PCA) is a multivariate analysis technique whose goal is to reduce the dimensionality of a large number of interrelated variables. It belongs to the class of projection methods and achieves its objective by calculating one or more linear combinations of the original set of maximum variance. [Source: Encyclopedia of Measurement and Statistics; Principal Component Analysis]
Concepto genérico
Pertenece al grupo
URI
http://data.loterre.fr/ark:/67375/N9J-WCFK2FX0-N
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