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30 lines
1.1 KiB
Matlab
30 lines
1.1 KiB
Matlab
10 years ago
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function numgrad = computeNumericalGradient(J, theta)
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%COMPUTENUMERICALGRADIENT Computes the gradient using "finite differences"
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%and gives us a numerical estimate of the gradient.
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% numgrad = COMPUTENUMERICALGRADIENT(J, theta) computes the numerical
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% gradient of the function J around theta. Calling y = J(theta) should
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% return the function value at theta.
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% Notes: The following code implements numerical gradient checking, and
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% returns the numerical gradient.It sets numgrad(i) to (a numerical
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% approximation of) the partial derivative of J with respect to the
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% i-th input argument, evaluated at theta. (i.e., numgrad(i) should
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% be the (approximately) the partial derivative of J with respect
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% to theta(i).)
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%
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numgrad = zeros(size(theta));
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perturb = zeros(size(theta));
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e = 1e-4;
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for p = 1:numel(theta)
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% Set perturbation vector
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perturb(p) = e;
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loss1 = J(theta - perturb);
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loss2 = J(theta + perturb);
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% Compute Numerical Gradient
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numgrad(p) = (loss2 - loss1) / (2*e);
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perturb(p) = 0;
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end
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end
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