dataset.asv

支持向量机的工具箱,功能比较齐全,安装在MATLAB的TOOBOX目录里面即可

function [xapp,yapp,xtest,ytest,xtest1,xtest2]=dataset(n,nbapp,nbtest,sigma)

% Usage
% [xapp,yapp,xtest,ytest,xtest1,xtest2]=dataset(String,nbapp,nbtest,sigma)
%
%
%  possible dataset creation
%  
%    'Mixture'  : 2 classes         
%          First class is a a mixture of gaussian
%          which takes in sandwiches the second class 
%
%           
%  'Gaussian' : is a classical dataset with two gaussianly distributed
%         classes with similar variances but different means
%
%  'Checkers': Checkers
%
%  'MultiClassCheckers'
%          
%  'Clowns' : The Clowns
%
%   'CosExp': sign( 0.95*cos(0.5*(exp(x)-1)))); for x in [0...4]
%       xtest1,xtest2 meshgrid of xtest

xapp=[];
yapp=[];
xtest=[];
ytest=[];
xtest1=[];
xtest2=[];
switch lower(n)
    
case 'mixture'
    
    %------------------Data Learn Generation -------------------------
    if nargin <4
        sigma=0.4;
    end;
    nbapp=round(nbapp/3);
    x1=sigma*randn(1,nbapp)+0.3;
    x2=sigma*randn(1,nbapp)-0.3;
    x3=sigma*randn(1,nbapp)-1;
    y1=sigma*randn(1,nbapp)+0.5;
    y2=sigma*randn(1,nbapp)-0.5;
    y3=sigma*randn(1,nbapp)-1;
    
    xapp=[x1 x2 x3; y1 y2 y3]';
    yapp=[ones(1,nbapp) -ones(1,nbapp) ones(1,nbapp)]';
    
    
    %----------------Data Test Generation ---------------------------
    nbtest=round(nbtest/3);
    xt=sigma*randn(1,nbtest)+0.3;
    xt2=sigma*randn(1,nbtest)-0.3;
    xt3=sigma*randn(1,nbtest)-1;
    yt=sigma*randn(1,nbtest)+0.5+0.7*xt;
    yt2=sigma*randn(1,nbtest)-0.5;
    yt3=sigma*randn(1,nbtest)-1-0.7*xt;
    xtest=[xt xt2 xt3; yt yt2 yt3]';
    
    
    ytest=[ones(1,nbtest) -ones(1,nbtest) ones(1,nbtest)]';
    return
case 'gaussian'
    nbapp=round(nbapp/2);
    nbtest=round(nbtest/2);
    if nargin <4
        sigma=0.2;
    end;
    x1=sigma*randn(1,nbapp)+0.3;
    x2=sigma*randn(1,nbapp)-0.3;
    y1=sigma*randn(1,nbapp)+0.5;
    y2=sigma*randn(1,nbapp)-0.5;
    xapp=[x1 x2; y1 y2]';
    yapp=[ones(1,nbapp) -ones(1,nbapp)]';
    x1=sigma*randn(1,nbtest)+0.3;
    x2=sigma*randn(1,nbtest)-0.3;
    y1=sigma*randn(1,nbtest)+0.5;
    y2=sigma*randn(1,nbtest)-0.5;
    xtest=[x1 x2; y1 y2]';
    ytest=[ones(1,nbtest) -ones(1,nbtest)]';
    
case 'checkers'
    xapp=[];
    yapp=[];
    nb=floor(nbapp/16);
    for i=-2:1;
        for j=-2:1;
            xapp=[xapp; [i+rand(nb,1) j+rand(nb,1)]];
            %(2*rem((i+j+4),2)-1)
            yapp=[yapp; (2*rem((i+j+4),2)-1)*ones(nb,1)];
        end;
    end;
    xtest=[];
    ytest=[];
    nb=floor(nbtest/16);
    for i=-2:1;
        for j=-2:1;
            xtest=[xtest; [i+rand(nb,1) j+rand(nb,1)]];
            %(2*rem((i+j+4),2)-1)
            ytest=[ytest; (2*rem((i+j+4),2)-1)*ones(nb,1)];
        end;
    end;
    %     [xt1,xt2]=meshgrid(linspace(-2,2,sqrt(nbtest)));
    %     [na,nb]=size(xt1);
    %     xtest1=reshape(xt1,na*nb,1);
    %     xtest2=reshape(xt2,na*nb,1);
    %     xtest=[xtest1 xtest2];
    %     ytest=zeros(length(xtest),1);
    %     for i=-2:1
    %         for j=-2:1
    %             pos=find( xtest(:,1)>=i & xtest(:,1)< i+1 & xtest(:,2)>=j & xtest(:,2)< j+1 );
    %             ytest(pos)=(2*rem((i+j+4),2)-1)*ones(length(pos),1);
    %         end;
    %     end;
    %     xtest1=reshape(xt1,na,nb);
    %     xtest2=reshape(xt2,na,nb);
    
    
    
case 'clowns'
    nbapp=round(nbapp/2);
    nbtest=round(nbtest/2);
    
    x1 = (6*rand(nbapp,1)-3); 
    x2 = x1.^2 + randn(nbapp,1); 
    x0 = sigma*randn(nbapp,2)+(ones(nbapp,1)*[0 6]); 
    xapp = [x0;[x1 x2]]; 
    xapp = (xapp-ones(2*nbapp,1)*mean(xapp))*diag(1./std(xapp)); 
    yapp = [ones(nbapp,1); -ones(nbapp,1)]; 
    
    if nbtest>0
        x1 = (6*rand(nbtest,1)-3); 
        x2 = x1.^2 + randn(nbtest,1); 
        x0 = sigma*randn(nbtest,2)+(ones(nbtest,1)*[0 6]); 
        xtest = [x0;[x1 x2]]; 
        xtest = (xtest-ones(2*nbtest,1)*mean(xtest))*diag(1./std(xtest)); 
        ytest = [ones(nbtest,1); -ones(nbtest,1)]; 
    end;
    
    
    
    
case 'cosexp'
    
    
%     freq=4;
%     nbtest=floor(sqrt(nbtest));
%     [xi]=rand(nbapp,2);
%     yapp= sign(0.95*cos(0.5*(exp(freq*xi(:,1))-1))-(2*xi(:,2)-1));
%     xapp = [5*xi(:,1) (2*xi(:,2)-1)];
%     [xtest1 xtest2]  = meshgrid(linspace(0,4,nbtest),linspace(-1,1,nbtest)); 
%     nn = length(xtest1); 
%     xtest = [reshape(xtest1 ,nn*nn,1) reshape(xtest2 ,nn*nn,1)]; 
%     ytest = sign(0.95*cos(0.5*(exp(freq*xtest(:,1))-1))-(2*xtest(:,2)-1));
%     
    
    freq=3;
    nbtest=floor(sqrt(nbtest));
    xapp=rand(nbapp,2);
    aux=0.95*cos((exp(freq*xapp(:,1))-1))  + sigma*randn(nbapp,1);
    yapp=sign(aux- (2*xapp(:,2)-1));
    xtest=[];
    ytest=[];
case 'multiclasscheckers'
    xapp=[];
    yapp=[];
    nb=floor(nbapp/16);
    % keyboard
    for i=-2:1;
        for j=-2:1;
            xapp=[xapp; [i+rand(nb,1) j+rand(nb,1)]];
            
            
            if rem(abs(i),2)==0 & rem(abs(j),2)==0
                yapp=[yapp; 1*ones(nb,1)];
            elseif rem(abs(i),2)==1 & rem(abs(j),2)==0
                yapp=[yapp; 2*ones(nb,1)];
            elseif rem(abs(i),2)==0 & rem(abs(j),2)==1
                yapp=[yapp; 3*ones(nb,1)];
            elseif rem(abs(i),2)==1 & rem(abs(j),2)==1
                yapp=[yapp; 4*ones(nb,1)];  
            end;
            
        end;
    end;
    xtest=[];
    
    [xt1,xt2]=meshgrid(linspace(-2,2,sqrt(nbtest)));
    [na,nb]=size(xt1);
    xtest1=reshape(xt1,na*nb,1);
    xtest2=reshape(xt2,na*nb,1);
    xtest=[xtest1 xtest2];
    ytest=zeros(length(xtest),1);
    for i=-2:1
        for j=-2:1
            pos=find( xtest(:,1)>=i & xtest(:,1)< i+1 & xtest(:,2)>=j & xtest(:,2)< j+1 );
            %ytest(pos)=(2*rem((i+j+4),2)-1)*ones(length(pos),1);
            if rem(abs(i),2)==0 & rem(abs(j),2)==0
                ytest(pos)=1*ones(length(pos),1);
            elseif rem(abs(i),2)==1 & rem(abs(j),2)==0
                ytest(pos)=2*ones(length(pos),1);
            elseif rem(abs(i),2)==0 & rem(abs(j),2)==1
                ytest(pos)=3*ones(length(pos),1);
            elseif rem(abs(i),2)==1 & rem(abs(j),2)==1
                ytest(pos)=4*ones(length(pos),1);
            end;
            
            
        end;
    end;
    xtest1=reshape(xt1,na,nb);
    xtest2=reshape(xt2,na,nb);
    
    
case 'multiclassgaussian'
    
    
    
    mean1=[1 1];
    mean2=[-1 1];
    mean3= [0 -1];
    x1=sigma*randn(nbapp,2)+ones(nbapp,1)*mean1;
    y1= ones(nbapp,1);
    x2=sigma*randn(nbapp,2)+ones(nbapp,1)*mean2;
    y2=2*ones(nbapp,1);
    x3=sigma*randn(nbapp,2)+ones(nbapp,1)*mean3;
    y3=3*ones(nbapp,1);
    Ytarget=[1 2 3];
    xapp=[x1;x2;x3];
    yapp=[y1;y2;y3];
    nbapp=size(xapp,1);
    
    
    %----------------Data Test Generation ---------------------------
    x1=sigma*randn(nbtest,2)+ones(nbtest,1)*mean1;
    y1= ones(nbtest,1);
    x2=sigma*randn(nbtest,2)+ones(nbtest,1)*mean2;
    y2=2*ones(nbtest,1);
    x3=sigma*randn(nbtest,2)+ones(nbtest,1)*mean3;
    y3=3*ones(nbtest,1);
    Ytarget=[1 2 3];
    xtest=[x1;x2;x3];
    ytest=[y1;y2;y3];
    nbapp=size(xapp,1);
    
case 'westonnonlinear' % dataset used in the Weston FeatSel Paper
    nbapp=round(nbapp/2);
    yapp = [ones(nbapp,1); -ones(nbapp,1)]; 
    
    A=2*(rand(2*nbapp,1)<0.5)-1;
    xapp=randn(2*nbapp,2) + [3*A A.*(yapp*1.875+1.125)];
    xapp = [xapp  20*randn(nbapp*2,8)];
    nbtest=round(nbtest/2);
    ytest = [ones(nbtest,1); -ones(nbtest,1)]; 
    A=2*(rand(2*nbtest,1)<0.5)-1;
    xtest=randn(2*nbtest,2) + [3*A A.*(ytest*1.875+1.125)];
    xtest = [xtest  20*randn(nbtest*2,8)];
    
    
case 'gaussianmultires'
    n=floor(nbapp/12);
    
    xm1=1;
    % The Big One
    mean1=[-xm1 -xm1];
    mean2=[xm1 xm1];
    sigma1=0.8;
        sigma2=0.3;
    xapp1=ones(2*n,1)* mean1+sigma1*randn(2*n,2);
    xapp2=ones(2*n,1)* mean2+sigma1*randn(2*n,2);
    yapp1=ones(n,1);
    yapp2=-ones(n,1);
    % The small ones
    mean1=[-2*xm1 0];
    mean2=[0 -2*xm1];
    mean3=[-2*xm1 -2*xm1];
    mean4=[-2*xm1 -2*xm1];

    xapp11=ones(n,1)* mean1+sigma2*randn(n,2);
    xapp12=ones(n,1)* mean2+sigma2*randn(n,2);
    xapp13=ones(n,1)* mean3+sigma2*randn(n,2);
    xapp14=ones(n,1)* mean4+sigma2*randn(n,2);
    % The small ones
    mean1=[2*xm1 0];
    mean2=[0 2*xm1];
    mean3=[2*xm1 2*xm1];
    mean4=[2*xm1 2*xm1];
 
    xapp21=ones(n,1)* mean1+sigma2*randn(n,2);
    xapp22=ones(n,1)* mean2+sigma2*randn(n,2);
    xapp23=ones(n,1)* mean3+sigma2*randn(n,2);
    xapp24=ones(n,1)* mean4+sigma2*randn(n,2);
     xapp=[xapp1;xapp21;xapp22;xapp23;xapp24;xapp2;xapp11;xapp12;xapp13;xapp14];
    yapp=[ones(6*n,1);-ones(6*n,1)];


%        mean1=[-1 1];
%     mean2=[-0.25 0.25];
%     mean3=[0.25 -0.25];
%     mean4=[+1 -1];
%     sigma3=sigma2;
%     sigma4=sigma1;
%     xapp1=ones(n,1)* mean1+sigma1*randn(n,2);
%     xapp2=ones(n,1)* mean2+sigma2*randn(n,2);
%     xapp3=ones(n,1)* mean3+sigma3*randn(n,2);
%     xapp4=ones(n,1)* mean4+sigma4*randn(n,2);
%     yapp1=-ones(n,1);
%     yapp2=ones(n,1);
%     yapp3=-ones(n,1);
%     yapp4=ones(n,1);
%         xapp=[xapp; xapp1;xapp2;xapp3;xapp4];
%     yapp=[yapp;yapp1;yapp2;yapp3;yapp4];
%     
    
    
    xtest=[];
    ytest=[];
    
 case 'carpette'
     xapp=2*rand(nbapp,2)-1;
     xtest=2*rand(nbtest,2)-1;
     xapp(find(sum(xapp.^2,2)>0.64),:)=[];
     xtest(find(sum(xtest.^2,2)>0.64),:)=[];
     
     yapp = carpette(xapp);
     ytest = carpette(xtest); 
     
 case 'gaussianmultires2'

     n=floor(nbapp/10);
     sigma=1.5;
     
     xapp=sigma*randn(6*n,2);
     rayon2=sum(xapp.^2,2);
     ind=find(rayon2 > 0.14 & rayon2 < 0.64); 
     yapp=ones(6*n,1);
     yapp(ind)=-ones(length(ind),1);
     
     mean1=[-4 0];
      mean2=[-0 4];
    mean3=[4 0];
    mean4=[0 -4];
    sigma1=0.5;
    xapp1=ones(n,1)* mean1+sigma1*randn(n,2);
    xapp2=ones(n,1)* mean2+sigma1*randn(n,2);
    xapp3=ones(n,1)* mean3+sigma1*randn(n,2);
    xapp4=ones(n,1)* mean4+sigma1*randn(n,2);
     xapp=[xapp;xapp1;xapp2;xapp3;xapp4];
     yapp=[yapp;-ones(4*n,1)];
     
     
     
end;
% ======================================
function color = carpette(x);

color = ones(length(x),1);
r2 = x(:,1).*x(:,1) +x(:,2).*x(:,2) ;
r2(find(r2<0.04)) = 10;
c2 = find(r2<0.25);
color(c2(find(x(c2,1)>=0))) = -1;
r2(c2) = 10;
c2 = find(r2<0.64);
color(c2(find(x(c2,1)<0))) = -1;
r2(c2) = 10;
c2 = find(r2<10);
%color(c2(find(x(c2,2)<0))) = 3;
%color(c2(find(x(c2,2)>=0))) = 4;