principal component analysis
Sign in to saveAlso known as PCA, principal components analysis
conversion of a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components
Research
88,430 papers- What is principal component analysis?Nature biotechnology · 2008
- Principal Component Analysis (PCA).La Tunisie medicale · 2021
- Principal Component Analysis in Dental Research.The International journal of oral & maxillofacial implants · 2025
- Principal Component Analysis on Recurrent Venous Thromboembolism.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/Hemostasis · 2019
- Principal component analysis.Transfusion · 2018
via PubMed
~40 min read
Encyclopedic overview
PCA of a multivariate Gaussian distribution centered at (1, 3) with a standard deviation of 3 in roughly the (0.866, 0.5) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by the square root of the corresponding eigenvalue, and shifted so their tails are at the mean.
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.
Excerpted from Wikipedia’s “principal component analysis” article, available under the CC BY-SA 4.0 licence.