SVD and non-negative matrix factorization

Question

The SVD and NMF are seem to be very close, so the question: how can I obtain NMF of given matrix from its SVD decomposition?

I've tried to zero-in all negative parts of SVD decomposition, but this gives bad results and iterative approach (zero-in, correct, zero-in) does not help either. Am I missing something or there is no meaningful relation between SVD and NMF?

Answer 1

There is a good reference explaining the relation between PCA and NMF Same author suggested by reuns but with more interpretation

I have found some work done by Chris Ding showing relation between PCA to Clustering. Where PCA is clustering data based on variances while one type of clustering called K-means which cluster the data based on Euclidean Distances. From this point there are proves showing the relation between K-means clustering to NMF.

Brief ppt showing relation between formulas

Good Reference to start with

If the previous one is hard this is having a brief of it