How to use the gaussian process regression function in matlab 2015b ?

John Williams answered . 2025-07-11 11:13:33

      % True curve.
      fun = @(x) x.*sin(x);
      xx  = linspace(0,10,100)';
      yy  = fun(xx);

      % Example points (from doc). You can do xd = linspace(1,9,nd)' as well 
      % but you will get a different fit.    
      xd = [1,3,5,6,7,8]';
      yd = fun(xd);

      % Fit a GP model. Initialize 'Sigma' to a small value. A GP estimates
      % its parameters by maximizing the marginal log likelihood. Depending
      % on the data, the marginal log likelihood can have multiple local
      % optima corresponding to different interpretations of the data.
      % Initializing 'Sigma' to a small value discourages the high noise
      % variance interpretation of the data.
      gp = fitrgp(xd,yd,'KernelFunction','squaredexponential','sigma',0.1,'verbose',1);

      % Plot.
      figure(1); clf
      plot(xx,yy, 'r-.')
      hold on;

      [ypred,~,yint] = predict(gp,xx);

      plot(xx,ypred, 'g-');
      plot(xx,yint(:,1),'k-');
      plot(xx,yint(:,2),'m-');

      plot(xd,yd,'ro');

      legend('f(x) = x.*sin(x)','GPR predictions','Lower 95% interval','Upper 95% interval','Observations','Location','Best');

 

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