Note
Click here to download the full example code or to run this example in your browser via Binder
Beta-divergence loss functions¶
A plot that compares the various Beta-divergence loss functions supported by
the Multiplicative-Update (‘mu’) solver in sklearn.decomposition.NMF.
import numpy as np
import matplotlib.pyplot as plt
from sklearn.decomposition._nmf import _beta_divergence
print(__doc__)
x = np.linspace(0.001, 4, 1000)
y = np.zeros(x.shape)
colors = 'mbgyr'
for j, beta in enumerate((0., 0.5, 1., 1.5, 2.)):
for i, xi in enumerate(x):
y[i] = _beta_divergence(1, xi, 1, beta)
name = "beta = %1.1f" % beta
plt.plot(x, y, label=name, color=colors[j])
plt.xlabel("x")
plt.title("beta-divergence(1, x)")
plt.legend(loc=0)
plt.axis([0, 4, 0, 3])
plt.show()
Total running time of the script: ( 0 minutes 0.422 seconds)
Estimated memory usage: 8 MB
