Coursera机器学习week6 编程作业

linearRegCostFunction.m

J = 1/(2*m)*sum((X*theta-y).^2)+lambda/(2*m)*(sum(theta.^2)-theta(1).^2);

grad = 1/m*X'*(X*theta-y)+lambda/m*theta;
grad(1) = grad(1) -lambda/m*theta(1)

learningCurve.m

for i = 1:m
	theta = trainLinearReg(X(1:i,:), y(1:i,:), lambda);
	error_train(i) = linearRegCostFunction(X(1:i,:), y(1:i,:), theta, 0); 
	error_val(i) = linearRegCostFunction(Xval, yval, theta, 0);
end

validationCurve.m

for i = 1 : length(lambda_vec)
	lambda = lambda_vec(i);
	theta = trainLinearReg(X, y, lambda);
	error_train(i) = linearRegCostFunction(X, y, theta, 0);
	error_val(i) = linearRegCostFunction(Xval, yval, theta, 0)
end