seniorPCA
What is the difference between PCA loadings and scores?
Updated May 17, 2026
Short answer
Loadings represent feature contributions, while scores represent transformed data points.
Deep explanation
PCA loadings are eigenvectors showing how much each original feature contributes to principal components. Scores are projections of original samples onto these components. Together they define transformation and representation of data.
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