continuousml / Non-Negative-Matrix-factorization---Implemented-in-python

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NMF Algorithm

Non-negative Matrix Factorisation (NMF): Family of linear algebra algorithms for identifying the latent structure in data represented as a non-negative matrix.

Input: matrix A; rank k.
Output: Two k-dimensional factors W and H approximating A
So our Objective function looks like this :




There are several approaches inorder to solve this minimization Problem. I used Multiplicative Update Method
introduced by Lee and Seung in 1999. (This Paper)

NNDSVD Method

As the Multiplicative Update is an iterative method, It is very senstive to initializations of W and H.
NNDSVD Method is a SVD based initialization, introduced by C. Boutsidis and E. Gallopoulos in 2007 (This Paper)

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