Linear Regression_最小二乘(LMS)

 %% Machine Learining----Linear Regression
 close all
 clear

 %%data load
 Year = linspace(,,);
 Price = [,2.5,2.9,3.147,4.515,4.903,5.365,5.704,6.853,7.791,8.561,,11.28,12.9];

 %%train data
 alpha = 0.01;
 theta = [,];
 obj_old = 1e10;
 tor = 1e-;

 tic;
 for time = :
     delta = zeros(,);
     objective = ;
     hypothesis = theta() + theta() * Year;
     drawnow;
     subplot(,,);
     plot(Year,Price,'rx',Year,hypothesis);
     for i = :
         delta = (theta() + theta() * Year(i) - Price(i)) * [,Year(i)] + delta;
         objective = (theta() + theta() * Year(i) - Price(i)) * (theta() + theta() * Year(i) - Price(i))+ objective;
     end
     theta = theta - alpha * delta / ;

     fprintf('objective is %.4f\n', objective);
     if abs(obj_old - objective) < tor
         fprintf('torlerance is samller than %.4f\n', tor);
         break;
     end
     obj_old = objective;
     subplot(,,);
     plot(toc,obj_old);
     axis([   ]) %xmin是x最小，xmax是x最大，ymin，ymax类似
     hold on;
 end