Jovian
Sign In
Learn practical skills, build real-world projects, and advance your career

Understand NMF using image and some random matrix

import numpy as np
X = np.random.randint(1,20,64).reshape(8,8)
from sklearn.decomposition import NMF
model = NMF(n_components=3, init='random', random_state=0)
W = model.fit_transform(X)
H = model.components_
W
array([[0.65908054, 2.46550098, 2.1994926 ],
       [0.        , 3.66329273, 1.87605977],
       [1.77254496, 0.        , 2.42391908],
       [2.4952005 , 3.51749554, 0.01527803],
       [1.3871326 , 2.72017775, 1.49985618],
       [0.18888674, 5.01174563, 0.36160411],
       [0.4253659 , 3.72835522, 2.04769359],
       [3.33135637, 1.78131666, 0.        ]])
H
array([[2.69715659e+00, 0.00000000e+00, 4.71903975e+00, 4.09038952e+00,
        3.01271305e-02, 1.21059719e+00, 4.96672930e+00, 2.43705579e+00],
       [0.00000000e+00, 3.68138679e+00, 8.06933225e-01, 1.56879319e+00,
        2.84038169e+00, 5.01040057e-01, 1.10147748e+00, 2.25174377e+00],
       [4.68183528e+00, 7.32343130e-01, 1.42166948e+00, 1.01440501e+00,
        7.85241464e-01, 7.10566802e+00, 6.14786871e-03, 0.00000000e+00]])
X
array([[10, 10,  9,  9,  8, 19,  5,  9],
       [12, 17,  8,  3, 12, 13,  5,  7],
       [19,  2, 13, 12,  1, 17,  4,  6],
       [ 3, 15, 19, 18, 10,  6, 15,  8],
       [ 8, 15, 13,  3,  8, 16, 18,  5],
       [ 6, 18,  5, 10, 13,  3,  2, 17],
       [ 8, 11,  2, 17, 15, 19,  7,  9],
       [12,  4, 13, 16,  6,  4, 19, 17]])