main.py

# see https://qiita.com/takechanman1228/items/6d1f65f94f7aaa016377

from sklearn.decomposition import NMF
import numpy as np

R = np.array([
        [5, 3, 0, 1],
        [4, 0, 0, 1],
        [1, 1, 0, 5],
        [1, 0, 0, 4],
        [0, 1, 5, 4]
    ])

for k in range(1, 4):
    model = NMF(n_components=k, init='random', random_state=0)
    P = model.fit_transform(R)
    Q = model.components_
    print("****************************")
    print("k:",k)
    print("Pは")
    print(P)
    print("Q^Tは")
    print(Q)
    print("P×Q^Tは")
    print(np.dot(P,Q))
    print("R-P×Q^Tは")
    print(model.reconstruction_err_)