Linear Regression exercise (Coursera course: ex1_multi)

Hi there,

I am taking Andrew Ng's Coursera class on machine learning. After implementing gradient descent in the first exercise (goal is to predict the price of a 1650 sq-ft, 3 br house), the J_history shows me a list of the same value (2.0433e+09). So when plotting the results, I am left with a straight line giving me that single value of J.

• Here is my code:

function [theta, J_history] = gradientDescentMulti(X, y, theta, alpha, num_iters)

m = length(y);

J_history = zeros(num_iters, 1);

for iter = 1:num_iters

    delta = zeros(size(X,2),1);

    for i=1:size(X,2)

        delta(i,1)=sum((theta'*X'-y').*(X(:,i))')*alpha/m;

    end

    theta = theta - delta;

    J_history(iter) = computeCostMulti(X, y, theta);

end

end

• What I entered in the Command Window:

data = load('ex1data2.txt');

X = data(:, 1:2);

y = data(:, 3);

m = length(y);

[X, mu, sigma] = featureNormalize(X)

X = [ones(m, 1) X];

std(X(:,2))

alpha = 0.01;

num_iters = 400;

theta = zeros(3, 1);

computeCostMulti(X,y,theta)

[theta, J_history] = gradientDescentMulti(X, y, theta, alpha, num_iters);

figure;

plot(1:numel(J_history), J_history, '-b', 'LineWidth', 2);

xlabel('Number of iterations');

ylabel('Cost J');

fprintf('Theta computed from gradient descent: \n');

fprintf(' %f \n', theta);

fprintf('\n');

I get the following result for theta: 340412.659574 110631.050279 -6649.474271

price = 0;

parameter = [1650,3];

parameter = (parameter-mu)./sigma;

parameter = [1,parameter];

price = theta'*parameter';

fprintf(['Predicted price of a 1650 sq-ft, 3 br house ' ... '(using gradient descent):\n $%f\n'], price);

I get the following result for the price: $293081.464335

• Here is the result for J_history:

I'm not sure where the issue comes from. I've attached the exercise and functions to this post.

Thanks for your help!

Pauline