Mercurial > hg > machine-learning-hw4

changeset 4:a1d62b2fd48d

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Comment out the pauses
author Jordi Gutiérrez Hermoso <jordigh@octave.org>
date Fri, 11 Nov 2011 17:50:32 -0500
parents 8e8089d5a55b
children 08072e7b3e9f
files ex4.m
diffstat 1 files changed, 16 insertions(+), 16 deletions(-) [+]
line wrap: on
line diff
--- a/ex4.m
+++ b/ex4.m
@@ -41,8 +41,8 @@
 
 displayData(X(sel, :));
 
-fprintf('Program paused. Press enter to continue.\n');
-pause;
+% fprintf('Program paused. Press enter to continue.\n');
+% pause;
 
 
 %% ================ Part 2: Loading Pameters ================
@@ -80,8 +80,8 @@
 fprintf(['Cost at parameters (loaded from ex4weights): %f '...
          '\n(this value should be about 0.287629)\n'], J);
 
-fprintf('\nProgram paused. Press enter to continue.\n');
-pause;
+% fprintf('\nProgram paused. Press enter to continue.\n');
+% pause;
 
 %% =============== Part 4: Implement Regularization ===============
 %  Once your cost function implementation is correct, you should now
@@ -99,8 +99,8 @@
 fprintf(['Cost at parameters (loaded from ex4weights): %f '...
          '\n(this value should be about 0.383770)\n'], J);
 
-fprintf('Program paused. Press enter to continue.\n');
-pause;
+% fprintf('Program paused. Press enter to continue.\n');
+% pause;
 
 
 %% ================ Part 5: Sigmoid Gradient  ================
@@ -116,8 +116,8 @@
 fprintf('%f ', g);
 fprintf('\n\n');
 
-fprintf('Program paused. Press enter to continue.\n');
-pause;
+% fprintf('Program paused. Press enter to continue.\n');
+% pause;
 
 
 %% ================ Part 6: Initializing Pameters ================
@@ -146,8 +146,8 @@
 %  Check gradients by running checkNNGradients
 checkNNGradients;
 
-fprintf('\nProgram paused. Press enter to continue.\n');
-pause;
+% fprintf('\nProgram paused. Press enter to continue.\n');
+% pause;
 
 
 %% =============== Part 8: Implement Regularization ===============
@@ -168,8 +168,8 @@
 fprintf(['\n\nCost at (fixed) debugging parameters (w/ lambda = 10): %f ' ...
          '\n(this value should be about 0.576051)\n\n'], debug_J);
 
-fprintf('Program paused. Press enter to continue.\n');
-pause;
+% fprintf('Program paused. Press enter to continue.\n');
+% pause;
 
 
 %% =================== Part 8: Training NN ===================
@@ -205,8 +205,8 @@
 Theta2 = reshape(nn_params((1 + (hidden_layer_size * (input_layer_size + 1))):end), ...
                  num_labels, (hidden_layer_size + 1));
 
-fprintf('Program paused. Press enter to continue.\n');
-pause;
+% fprintf('Program paused. Press enter to continue.\n');
+% pause;
 
 
 %% ================= Part 9: Visualize Weights =================
@@ -218,8 +218,8 @@
 
 displayData(Theta1(:, 2:end));
 
-fprintf('\nProgram paused. Press enter to continue.\n');
-pause;
+% fprintf('\nProgram paused. Press enter to continue.\n');
+% pause;
 
 %% ================= Part 10: Implement Predict =================
 %  After training the neural network, we would like to use it to predict