From 63c1523528dae7fa10878b0af3f6bc71765ff11b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Aur=C3=A9lien=20Geron?= Date: Thu, 7 Dec 2017 18:57:30 -0800 Subject: [PATCH] Replace n_inputs with n_outputs, fixes #125 --- 04_training_linear_models.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/04_training_linear_models.ipynb b/04_training_linear_models.ipynb index c0bea14..a32fdea 100644 --- a/04_training_linear_models.ipynb +++ b/04_training_linear_models.ipynb @@ -1909,7 +1909,7 @@ " error = Y_proba - Y_train_one_hot\n", " if iteration % 500 == 0:\n", " print(iteration, loss)\n", - " gradients = 1/m * X_train.T.dot(error) + np.r_[np.zeros([1, n_inputs]), alpha * Theta[1:]]\n", + " gradients = 1/m * X_train.T.dot(error) + np.r_[np.zeros([1, n_outputs]), alpha * Theta[1:]]\n", " Theta = Theta - eta * gradients" ] }, @@ -1987,7 +1987,7 @@ " l2_loss = 1/2 * np.sum(np.square(Theta[1:]))\n", " loss = xentropy_loss + alpha * l2_loss\n", " error = Y_proba - Y_train_one_hot\n", - " gradients = 1/m * X_train.T.dot(error) + np.r_[np.zeros([1, n_inputs]), alpha * Theta[1:]]\n", + " gradients = 1/m * X_train.T.dot(error) + np.r_[np.zeros([1, n_outputs]), alpha * Theta[1:]]\n", " Theta = Theta - eta * gradients\n", "\n", " logits = X_valid.dot(Theta)\n",