What is the computational complexity of PCA?

PCA complexity depends on SVD or eigen decomposition, typically O(min(n²p, np²)).

For data matrix X (n samples, p features), PCA using SVD has complexity O(min(n²p, np²)). Covariance-based methods add overhead of computing p×p matrix. Complexity increases significantly with high dimensionality.