testcross2d.m

一种快速的多叉搜索树

clear;
  % test for LWPR on 2D data set
  n = 5000;

  % a random training set using the CROSS function
  X = (rand(n,2)-.5)*2;
  Y = max([exp(-X(:,1).^2 * 10),exp(-X(:,2).^2 * 50),1.25*exp(-(X(:,1).^2+X(:,2).^2)*5)]');
  Y = Y' + randn(n,1)*0.1;

  % a systematic test set on a grid
  Xt = [];
  for i=-1:0.05:1,
    for j=-1:0.05:1,
      Xt = [Xt; i j];
    end
  end
  Yt = max([exp(-Xt(:,1).^2 * 10),exp(-Xt(:,2).^2 * 50),1.25*exp(-(Xt(:,1).^2+Xt(:,2).^2)*5)]');
  Yt = Yt';

N = size(X,1);
nXdim = size(X,2); 
nYdim = size(Y,2);  
q = 20;                  
knn = 1;                
freezeW = 40;            
x_quantize = 0.01;      
y_quantize = 0.1;        

disp('Train by using the sample set');
tid = createIHDRT(nXdim,nYdim,q,knn,freezeW,x_quantize,y_quantize);
for i=1:size(X,1) 
    ret = addPatternIHDRT(tid, X(i,:), Y(i,:));
end

disp('Test using the test set');
mse = 0;
for i=1:size(Xt,1)
    %[ret, Xout, Yout, dist] = RetrieveIHDRT(tid, Xt(i,:));
    %[ret,Yo1, Yo2]=regressionIHDRT2(tid,Xt(i,:),1, 1, 'knn',20, 'lambda', 0.01);
    [ret,Yout]=regressionIHDRT(tid,Xt(i,:),'knn',40, 'lambda', 0.1);
    %Yout=Yo1+Yo2;
    error(i) = (Yout - Yt(i))^2;
    mse = mse + (Yout - Yt(i))^2;
    Yp(i) = Yout;
end
Yp = Yp';
mse = mse/size(Xt,1)
%nmse =sqrt(mse/size(Xt,1));      %normalized mean square error

fprintf(1,'The fitted function: MSE=%5.3f',mse);

  figure(1);
  clf;
% plot the fitted surface
  axis([-1 1 -1 1 -.5 1.5]);
  subplot(2,1,1);
  [x,y,z]=makesurf([Xt,Yp],sqrt(length(Xt)));
  surfl(x,y,z);
  axis([-1 1 -1 1 -.5 1.5]);
  title(sprintf('The fitted function: MSE=%5.3f',mse));

  % plot the true surface
  subplot(2,1,2);
  [x,y,z]=makesurf([Xt,Yt],sqrt(length(Xt)));
  surfl(x,y,z);
  axis([-1 1 -1 1 -.5 1.5]);
  title('The true function');

closeIHDRT(tid);