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Regularized NN gradient

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neingeist 2014-11-02 13:48:34 +01:00
parent bdecab8cf8
commit eccdcc0d81
1 changed files with 7 additions and 3 deletions
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10
ex4/nnCostFunction.m
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@ -124,12 +124,16 @@ Theta1_grad = D_1;
% Note: Theta1/2 are matrixes here, we want all their rows, but skip their
% first column (not regularizing the bias term).
regularization_term = lambda/(2*m) * ...
J_regularization_term = lambda/(2*m) * ...
(sum(sum(Theta1(:,2:end).^2)) ...
+ sum(sum(Theta2(:,2:end).^2)));
assert(size(regularization_term) == [1 1]);
assert(size(J_regularization_term) == [1 1]);
J += J_regularization_term;
J += regularization_term;
Theta2_grad_regularization_term = lambda/m * [zeros(size(Theta2, 1), 1) Theta2(:,2:end)];
Theta1_grad_regularization_term = lambda/m * [zeros(size(Theta1, 1), 1) Theta1(:,2:end)];
Theta2_grad += Theta2_grad_regularization_term;
Theta1_grad += Theta1_grad_regularization_term;
% -------------------------------------------------------------