% Copyright (c) 2002,  KULeuven-ESAT-SCD, License & help @ http://www.esat.kuleuven.ac.be/sista/lssvmlabclcclearclose alldisp(' This demo illustrates how one can use different components ');disp(' of the toolbox to compose a fixed size LS-SVM classifier.');disp(' To study how this result can be achieved, study the used commands.');disp(' These can be shown by the command');disp(' ');disp(' >> type demo_fixedclass');disp(' ');disp(' or ');disp(' ');disp(' >> edit demo_fixedclass');disp(' ');nb = 1000;X = 2.*rand(nb,2)-1;Y = sign(sin(X(:,1))+X(:,2)+0.1.*rand(nb,1));[s,si] = sort(X(:,1));X = X(si,:); Y = Y(si,:);%% initiate valuestype = 'classification';gamma = 10;kernel = 'RBF_kernel';sigma2 = 0.2;crit_old=-inf;Nc=25;Xs=X(1:Nc,:);Ys=Y(1:Nc,:);%% Initiate grid for plotgrain = 25;xmin1=min(X(:,1)); xmax1=max(X(:,1)); xmin2=min(X(:,2)); xmax2=max(X(:,2)); xrange1 = xmin1:(xmax1-xmin1)/grain:xmax1;xrange2 = xmin2:(xmax2-xmin2)/grain:xmax2;[XX,YY] = meshgrid(xrange1,xrange2);Xt = [reshape(XX,prod(size(XX)),1) reshape(YY,prod(size(YY)),1)];figure;%% iterate over data%for tel=1:2*length(X)       %  % new candidate set  %  Xsp=Xs; Ysp=Ys;  S=ceil(length(X)*rand(1));  Sc=ceil(Nc*rand(1));  Xs(Sc,:) = X(S,:);  Ys(Sc,:) = Y(S);  Ncc=Nc;  %  % automaticly extract features and compute entropy  %  crit = kentropy(Xs,kernel, sigma2);    if crit <= crit_old,    crit = crit_old;    Xs=Xsp;    Ys=Ysp;  else    crit_old = crit;    %    % ridge regression        features   = AFE(Xs,kernel, sigma2,X);    features_t = AFE(Xs,kernel, sigma2,Xt);    [w,b,Yht] = ridgeregress(features,Y,gamma,features_t);    Yht = sign(Yht);    %    % make-a-plot    Ygt = reshape(Yht(:,1),size(XX,1),size(XX,2));    [C,h]=contourf(XX,YY,Ygt);     hold on;    n = find(Y<=0);    np = plot(X(n,1),X(n,2),'.c');     p = find(Y>0);    pp = plot(X(p,1),X(p,2),'.m');     sv = plot(Xs(:,1),Xs(:,2),'go','Linewidth',7);    xlabel('X_1'); ylabel('X_2');     title(['Approximation by fixed size LS-SVM based on maximal entropy: ' num2str(crit)]);    legend([np pp sv],'Negative points','Positive points',...           'Support Vectors');        hold off;  drawnow    end    end