Machine Learning, Data Science, Dimensionality Reduction, Svd, Linear Algebra.
To save space, S is returned as a 1D array of singular values instead of the complete 2D matrix. Truncated SVD in scikit-learn In most common applications, we do not want to find the complete matrices U, S and V. We saw this in dimensionality reduction and Latent Semantic Analysis, remember? We are