%SVC的二維回歸！！！
clc
clear all
global p1;
p1=2.111;
e=0.005;
C=2;
load forregression2.txt
x1=forregression2(1,:);
x2=forregression2(2,:);
X=[x1;x2];
X=X';
Y=forregression2(3,:);
Y=Y';
len=length(Y);
%畫出兩個不同的類別
  plot3(x1,x2,Y,'or');
  hold on;
  Box on;
[nsv, beta, bias] = svr(X,Y,'rbf',C,'eInsensitive',e);

x1=linspace(-4*pi,4*pi,100);
x1=x1';
x2=ones(100,1);
x2=x2*6.0;
testX=[1.1 1.1;2.0 1.84 ];
testX=[ x2 x1];
%predictedY = svcoutput(X,Y,testX,'rbf',alpha,b0,0);
tstY = svroutput(X,testX,'rbf',beta, bias)
len=length(tstY);
%畫出分類結果
%for i=1:len;
  plot3(testX(:,1),testX(:,2),tstY);
    %end
Box on;
%uiclass;