34 lines
1.1 KiB
Matlab
34 lines
1.1 KiB
Matlab
function [J, grad] = linearRegCostFunction(X, y, theta, lambda)
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%LINEARREGCOSTFUNCTION Compute cost and gradient for regularized linear
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%regression with multiple variables
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% [J, grad] = LINEARREGCOSTFUNCTION(X, y, theta, lambda) computes the
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% cost of using theta as the parameter for linear regression to fit the
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% data points in X and y. Returns the cost in J and the gradient in grad
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% Initialize some useful values
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m = length(y); % number of training examples
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% You need to return the following variables correctly
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J = 0;
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grad = zeros(size(theta));
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% ====================== YOUR CODE HERE ======================
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% Instructions: Compute the cost and gradient of regularized linear
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% regression for a particular choice of theta.
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%
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% You should set J to the cost and grad to the gradient.
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%
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reg = theta;
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reg(1) = 0;
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J = sum( (X*theta - y) .^ 2 ) / (2*m) + (lambda/(2*m))*sum(reg.^2);
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grad = (X' * (X*theta-y) / m) + (lambda/m) * reg;
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% =========================================================================
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grad = grad(:);
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end
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