Dimensionality Reduction Practice

Relate PCA variance objectives to covariance eigenvectors and SVD.

Recommended resources

Instructions

  1. Center the data conceptually before applying PCA.

Ordered items

  1. PCA direction and explained varianceDimensionality Reduction · 7 min
  2. Low-rank error and explained varianceLinear Algebra · 8 min

Completion

Explain both reconstruction-error and retained-variance views of PCA.