LearningInteractiveDimensionality reduction
PCA — Principal Component Analysis (Explained)
Learn PCA: variance, principal components, dimensionality reduction, and when to use it.
Welcome to PCA Explained!
PCA helps you reduce complexity while keeping the most important directions of variance. Generate a small dataset or upload one, then watch how the principal components emerge.
How it works
- Mean-center the data
- Compute principal components from the covariance matrix
- Project to 1..k components and inspect variance retained