What is randomized PCA and why is it used?

Randomized PCA approximates principal components using probabilistic algorithms for speed.

Randomized PCA uses random projections to approximate leading singular vectors efficiently. It reduces computational cost significantly while maintaining high accuracy, especially useful for large datasets.