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udlbook
2025-11-05 09:48:13 -05:00
parent 16b72a8a9e
commit 4a08818706
1 changed files with 2 additions and 2 deletions
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Notebooks/Chap06/6_2_Gradient_Descent.ipynb
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@@ -301,7 +301,7 @@
"source": [ "source": [
"def loss_function_1D(dist_prop, data, model, phi_start, search_direction):\n", "def loss_function_1D(dist_prop, data, model, phi_start, search_direction):\n",
" # Return the loss after moving this far\n", " # Return the loss after moving this far\n",
" return compute_loss(data[0,:], data[1,:], model, phi_start+ search_direction * dist_prop)\n", " return compute_loss(data[0,:], data[1,:], model, phi_start - search_direction * dist_prop)\n",
"\n", "\n",
"def line_search(data, model, phi, gradient, thresh=.00001, max_dist = 0.1, max_iter = 15, verbose=False):\n", "def line_search(data, model, phi, gradient, thresh=.00001, max_dist = 0.1, max_iter = 15, verbose=False):\n",
" # Initialize four points along the range we are going to search\n", " # Initialize four points along the range we are going to search\n",
@@ -365,7 +365,7 @@
"def gradient_descent_step(phi, data, model):\n", "def gradient_descent_step(phi, data, model):\n",
" # TODO -- update Phi with the gradient descent step (equation 6.3)\n", " # TODO -- update Phi with the gradient descent step (equation 6.3)\n",
" # 1. Compute the gradient (you wrote this function above)\n", " # 1. Compute the gradient (you wrote this function above)\n",
" # 2. Find the best step size alpha using line search function (above) -- use negative gradient as going downhill\n", " # 2. Find the best step size alpha using line search function (above)\n",
" # 3. Update the parameters phi based on the gradient and the step size alpha.\n", " # 3. Update the parameters phi based on the gradient and the step size alpha.\n",
"\n", "\n",
" return phi" " return phi"