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Calculates cost successfully
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@@ -40,20 +40,11 @@ Theta_grad = zeros(size(Theta));
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% partial derivatives w.r.t. to each element of Theta
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%
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t1 = (Theta*X')';
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t2 = (t1-Y).^2;
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t3 = t2(R==1);
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temp = sum(t3(:));
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J = (1/2) * (temp);
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% =============================================================
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@@ -40,7 +40,7 @@ ylabel('Movies');
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xlabel('Users');
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fprintf('\nProgram paused. Press enter to continue.\n');
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pause;
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% pause;
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%% ============ Part 2: Collaborative Filtering Cost Function ===========
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% You will now implement the cost function for collaborative filtering.
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@@ -66,7 +66,7 @@ fprintf(['Cost at loaded parameters: %f '...
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'\n(this value should be about 22.22)\n'], J);
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fprintf('\nProgram paused. Press enter to continue.\n');
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pause;
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% pause;
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%% ============== Part 3: Collaborative Filtering Gradient ==============
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