[Statistics] Derivation of Principal Component Anaylsis (PCA)

Principal Component Anaylsis (PCA)

• Identify the axes, known as principal components, that capture the most significant patterns in the original distribution of the data
  • axes (eigenvectors of covariance matrix) with maximum eigenvalues
  • every principal components are orthogonal to each other

Derivation

• Derivation of PCA