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Non-negative matrix factorization - Wikipedia NMF generates factors with significantly reduced dimensions compared to the original matrix For example, if V is an m × n matrix, W is an m × p matrix, and H is a p × n matrix then p can be significantly less than both m and n
NMF: A Flexible R package for Nonnegative Matrix Factorization Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face recognition and text mining
NMF — scikit-learn 1. 7. 2 documentation Non-Negative Matrix Factorization (NMF) Find two non-negative matrices, i e matrices with all non-negative elements, (W, H) whose product approximates the non-negative matrix X