基于
//www.tianjin-qmedu.com/matlabcentral/fileexchange/6716-orthogonal-linear-regression

http://en.wikipedia.org/wiki/Linear_least_squares

http://www.youtube.com/watch?v=5u4G23_OohI

使用
%准备一些数据
xdata = 0:0.1:10;
ydata = 2 + 7 * xdata + 6 * randn(大小(xdata));

%与普通线性回归
p0 = polyfit (xdata ydata 1);
yy0 = polyval (p0, xdata);
%与线性符合情节比较数据

% %我的函数
ξ= xdata;易= ydata, theta_st = [0 0]; nsteps = 150; mindiff = 1 e - 3; learnrate = 1 e-5;
[theta_out, err_vec theta_vec] = gradient_descent_opt (xi,咦,theta_st、nsteps mindiff, learnrate);
theta_out ygrad = theta_out (1) + (2) * xdata;

图(1)
情节(xdata ydata,“。”, xdata, ygrad, xdata, yy0,“:”);
包含(“x”); ylabel (y)
标题(“。org: polyval, r)