多变量线性回归~疑问版

%% ================ Part 1: Feature Normalization ================

%% Clear and Close Figures

clear ; close all; clc

fprintf('Loading data ...\n');

data = load('ex1data2.txt');

X = data(:, 1:2);

y = data(:, 3);

m = length(y);

plot(X, y, 'rx', 'MarkerSize', 10);

pause;

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

% Add intercept term to X

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

%% ================ Part 2: Gradient Descent ================

fprintf('Running gradient descent ...\n');

% Choose some alpha value

alpha = 0.01;

num_iters = 400;

% Init Theta and Run Gradient Descent

theta = zeros(3, 1);

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

% Plot the convergence graph

figure;

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

xlabel('Number of iterations');

ylabel('Cost J');

% Display gradient descent's result

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

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

fprintf('\n');

% Estimate the price of a 1650 sq-ft, 3 br house

% ====================== YOUR CODE HERE ======================

% Recall that the first column of X is all-ones. Thus, it does

% not need to be normalized.

te = [1650 3];

te = te - mu;

te = te ./ sigma;

price = [1 te]*theta;% You should change this

这里我算出来是0？！！！

% ============================================================

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

fprintf('Program paused. Press enter to continue.\n');

pause;

%% ================ Part 3: Normal Equations ================

fprintf('Solving with normal equations...\n');

% ====================== YOUR CODE HERE ======================

% Instructions: The following code computes the closed form

%               solution for linear regression using the normal

%               equations. You should complete the code in

%               normalEqn.m

%

%               After doing so, you should complete this code

%               to predict the price of a 1650 sq-ft, 3 br house.

%

%% Load Data

data = csvread('ex1data2.txt');

X = data(:, 1:2);

y = data(:, 3);

m = length(y);

% Add intercept term to X

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

% Calculate the parameters from the normal equation

theta = normalEqn(X, y);

% Display normal equation's result

fprintf('Theta computed from the normal equations: \n');

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

fprintf('\n');

% Estimate the price of a 1650 sq-ft, 3 br house

% ====================== YOUR CODE HERE ======================

price = 0; % You should change this

% ============================================================

fprintf(['Predicted price of a 1650 sq-ft, 3 br house ' ...

'(using normal equations):\n $%f\n'], price);

正规化方法？（上图）