This is a matrix approximation algorithm that randomly selects smaller subsets of available data to compute a truncated SVD matrix close to the actual SVD. It is used in big data applications and time-series prediction.
This is a matrix approximation algorithm that randomly selects smaller subsets of available data to compute a truncated SVD matrix close to the actual SVD. It is used in big data applications and time-series prediction.