Kernel Principal Component Analysis - Linear PCA

Linear PCA

Recall that conventional PCA operates on zero-centered data; that is,

.

It operates by diagonalizing the covariance matrix,

in other words, it gives an eigendecomposition of the covariance matrix:

which can be rewritten as

.

(See also: Covariance matrix as a linear operator)