Non-negative matrix factorization (NMF), also non-negative matrix approximation is a group of algorithms in multivariate analysis and linear algebra where a matrix V is factorized into (usually) two matrices W and H, with the property that all three matrices have no negative elements. This non-negativity makes the resulting matrices easier to inspect. Since the problem is not exactly solvable in general, it is commonly approximated numerically. NMF finds applications in such fields as computer vision, document clustering, chemometrics and recommender systems. … Non-negative Matrix Factorization (NMF)

# If you did not already know: “Non-negative Matrix Factorization (NMF)”

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