Hi Raphael,
The other matrix in the factorization is the output of nmf.transform(A).
In your example you forgot to fit the estimator; if you're just
interested in the decomposition the recommended way is to get it in
one line with W = nmf.fit_transform(A).
While the mathematical description doesn
I am trying to use NMF from scikit learn. Given a matrix A this should
give me a factorization into matrices W and H so that WH is
approximately equal to A. As a sanity check I tried the following:
from sklearn.decomposition import NMF
import numpy as np
A = np.array([[0,1,0],[1,0,1],[1,1,0]])
nmf
