www.pudn.com > myMatlabfenlei.rar > svrplot.m

function svrplot(X,Y,ker,beta,bias,e,mag,xaxis,yaxis,input) 
%SVRPLOT Support Vector Regression Plotting routine for 1D function 
% 
%  Usage: svrplot(X,Y,ker,alpha,bias,e,mag,xaxis,yaxis,input) 
% 
%  Parameters: X      - Training inputs 
%              Y      - Training targets 
%              ker    - kernel function 
%              beta   - Difference of Lagrange Multipliers 
%              bias   - Bias term  
%              e      - e insensitive value 
%              mag    - display magnification  
%              xaxis  - xaxis input (default: 1)  
%              input  - vector of input values (default: zeros(no_of_inputs)) 
% 
%  Author: Steve Gunn (srg@ecs.soton.ac.uk) 
 
  if (nargin < 5 | nargin > 8) % check correct number of arguments 
    help svrplot 
  else 
 
    epsilon = 1e-4;   
    if (nargin < 9) input = zeros(1,size(X,2));, end 
    if (nargin < 8) xaxis = 1;, end 
    if (nargin < 7) mag = 0;, end 
    if (nargin < 6) e = 0;, end 
     
    xmin = min(X(:,xaxis));, xmax = max(X(:,xaxis));  
    xa = (xmax - xmin);, xmin = xmin - mag*xa;, xmax = xmax + mag*xa; 
 
    % Plot function value 
 
    n = size(X,1); 
    x = [xmin:(xmax-xmin)/300:xmax];  
    z = bias*ones(size(x)); 
    for x1 = 1 : length(x) 
      input(xaxis) = x(x1); 
      for i = 1 : length(Y) 
          if (abs(beta(i)) > epsilon) 
    	    z(x1) = z(x1) + beta(i)*svkernel(ker,input,X(i,:)); 
          end 
      end 
    end 
    plot(x,z,'k','linewidth',2); 
    axis off 
    hold on 
     
    % Plot e insensitive zone 
    if (e > 0) 
       plot(x,z+e,'b:') 
       plot(x,z-e,'b:') 
    end 
  
    % Plot Training points 
     
    for i = 1:size(Y) 
      plot(X(i),Y(i),'k+')  
      if (abs(beta(i)) > epsilon) 
        plot(X(i),Y(i),'ro','markersize',10) % Support Vector 
      end 
    end 
    set(gca,'XLim',[xmin xmax]);   
    hold off 
 
  end