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Update 5_1_Least_Squares_Loss.ipynb

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udlbook
2023-12-17 17:49:34 -05:00
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parent c56251df11
commit aa04c283e8
1 changed files with 3 additions and 3 deletions
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Notebooks/Chap05/5_1_Least_Squares_Loss.ipynb
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@@ -539,8 +539,8 @@
"# Hopefully, you can see that the maximum of the likelihood fn is at the same position as the minimum negative log likelihood\n", "# Hopefully, you can see that the maximum of the likelihood fn is at the same position as the minimum negative log likelihood\n",
"# The least squares solution does not depend on sigma, so it's just flat -- no use here.\n", "# The least squares solution does not depend on sigma, so it's just flat -- no use here.\n",
"# Let's check that:\n", "# Let's check that:\n",
"print(\"Maximum likelihood = %3.3f, at beta_1=%3.3f\"%( (likelihoods[np.argmax(likelihoods)],sigma_vals[np.argmax(likelihoods)])))\n", "print(\"Maximum likelihood = %3.3f, at sigma=%3.3f\"%( (likelihoods[np.argmax(likelihoods)],sigma_vals[np.argmax(likelihoods)])))\n",
"print(\"Minimum negative log likelihood = %3.3f, at beta_1=%3.3f\"%( (nlls[np.argmin(nlls)],sigma_vals[np.argmin(nlls)])))\n", "print(\"Minimum negative log likelihood = %3.3f, at sigma=%3.3f\"%( (nlls[np.argmin(nlls)],sigma_vals[np.argmin(nlls)])))\n",
"# Plot the best model\n", "# Plot the best model\n",
"sigma= sigma_vals[np.argmin(nlls)]\n", "sigma= sigma_vals[np.argmin(nlls)]\n",
"y_model = shallow_nn(x_model, beta_0, omega_0, beta_1, omega_1)\n", "y_model = shallow_nn(x_model, beta_0, omega_0, beta_1, omega_1)\n",
@@ -564,4 +564,4 @@
} }
} }
] ]
} }