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Update 8_2_Bias_Variance_Trade_Off.ipynb

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Pietro Monticone
2023-10-30 17:59:24 +01:00
parent 008b058b14
commit cd76e76ad2
1 changed files with 3 additions and 3 deletions
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Notebooks/Chap08/8_2_Bias_Variance_Trade_Off.ipynb
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@@ -77,7 +77,7 @@
" for i in range(n_data):\n", " for i in range(n_data):\n",
" x[i] = np.random.uniform(i/n_data, (i+1)/n_data, 1)\n", " x[i] = np.random.uniform(i/n_data, (i+1)/n_data, 1)\n",
"\n", "\n",
" # y value from running through functoin and adding noise\n", " # y value from running through function and adding noise\n",
" y = np.ones(n_data)\n", " y = np.ones(n_data)\n",
" for i in range(n_data):\n", " for i in range(n_data):\n",
" y[i] = true_function(x[i])\n", " y[i] = true_function(x[i])\n",
@@ -229,7 +229,7 @@
" y_model_all = np.zeros((n_datasets, x_model.shape[0]))\n", " y_model_all = np.zeros((n_datasets, x_model.shape[0]))\n",
"\n", "\n",
" for c_dataset in range(n_datasets):\n", " for c_dataset in range(n_datasets):\n",
" # TODO -- Generate n_data x,y, pairs with standard divation sigma_func\n", " # TODO -- Generate n_data x,y, pairs with standard deviation sigma_func\n",
" # Replace this line\n", " # Replace this line\n",
" x_data,y_data = np.zeros([1,n_data]),np.zeros([1,n_data])\n", " x_data,y_data = np.zeros([1,n_data]),np.zeros([1,n_data])\n",
"\n", "\n",
@@ -316,7 +316,7 @@
"\n", "\n",
" # Compute variance -- average of the model variance (average squared deviation of fitted models around mean fitted model)\n", " # Compute variance -- average of the model variance (average squared deviation of fitted models around mean fitted model)\n",
" variance[c_hidden] = 0\n", " variance[c_hidden] = 0\n",
" # Compute bias (average squared deviaton of mean fitted model around true function)\n", " # Compute bias (average squared deviation of mean fitted model around true function)\n",
" bias[c_hidden] = 0\n", " bias[c_hidden] = 0\n",
"\n", "\n",
"# Plot the results\n", "# Plot the results\n",