domains / families / data / pca-decomposition

pca-decomposition

separate

Reduce dimensionality of multivariate data using PCA with varimax rotation. Use when you have many correlated variables and need to identify underlying factors or reduce collinearity.

When to use

• Many correlated predictor variables
• Need to identify underlying factor groups
• Reduce multicollinearity before regression
• Exploratory data analysis

When not to use

• Running separate PCA for each category

Skill page

Source