A plot that compares the various Beta-divergence loss functions supported by the Multiplicative-Update (‘mu’) solver in sklearn.decomposition.NMF
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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 0.345 seconds)
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http://scikit-learn.org/stable/auto_examples/decomposition/plot_beta_divergence.html