Principal component analysis (PCA) Machine Learning
noun phrase
Definition: A statistical dimensionality-reduction technique that transforms correlated variables into a smaller set of linearly uncorrelated variables called principal components, ordered by explained variance [scikit-learn Documentation].
Example in context: “Principal Component Analysis is now one of the age-old and well-established methods for feature reduction.” [Joshi, Haspel 2020]
Synonym: PCA
Related terms: dimensionality reduction; feature extraction; orthogonal components; explained variance; singular value decomposition (SVD); kernel PCA.