PCA selects low-dimensional linear surfaces to maximize the captured variance.

PCA selects low-dimensional linear surfaces to maximize the captured variance.

• A. PCA reduces dimensionality by projecting data onto a nonlinear surface.
• B. PCA reduces dimensionality by projecting data onto a linear surface that maximizes explained variance.
• C. PCA cannot be used for visualization.
• D. PCA guarantees perfect reconstruction.

Answer: (B)