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When the orthogonality constraint <math> \mathbf{H}\mathbf{H}^T = I </math> is not explicitly imposed, the orthogonality holds to a large extent, and the clustering property holds too. Clustering is the main objective of most [[data mining]] applications of NMF.{{citation needed|date=April 2015}}
When the error function to be used is [[Kullback–Leibler divergence]], NMF is identical to the [[Probabilistic latent semantic analysis]], a popular document clustering method.<ref>
== Types ==
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