Why do we use Non-negative matrix factorization?What is the advantage and superiority of other matrix decomposition methods?

  • $\begingroup$ Because: - it is an effective unsupervised method, so no training data are required. Performs clustering and outperforms many state-of-the-art methods, kmeans, knn,...- Successfully used in a wide range of applications. The nonnegativity condition makes the outputs interpretable without further processing, unlike PCA or SVD. - The optimization problem behind is adaptable, you add the needed constraints depending on the situation. $\endgroup$ Jul 14, 2021 at 15:49


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