Question: how does svd reduce dimension?
Answer: Using SVD for Dimensionality Reduction. SVD, or Singular Value Decomposition, is one of several techniques that can be used to reduce the dimensionality, i.e., the number of columns, of a data set. ... In predictive analytics, more columns normally means more time required to build models and score data.