testksvm.m

粒子群算法

function [y,t] = testKSVM(B1,A1,C1)
tic
   
  max_ev =15;  %选择主元个数
      rbf_var = 1;  %髙斯函数的参数
      cov_size=size(A1,1);     %样本个数
      for i=1:cov_size,    %得到K
          for j=i:cov_size,
              K(i,j) = exp(-norm(A1(i,:)-A1(j,:))^2/rbf_var);
              K(j,i) = K(i,j);
          end
      end
      unit = ones(cov_size, cov_size)/cov_size;
      % centering in feature space!
      K_n = K - unit*K - K*unit + unit*K*unit;

      [evecs,evals] = eig(K_n);
     % A2=evecs;
      evals = real(diag(evals));
      for i=1:cov_size,
          evecs(:,i) = evecs(:,i)/(sqrt(evals(i)));   
      end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
      test_num=size(A1,1);

      unit_test = ones(test_num,cov_size)/cov_size;
      K_test = zeros(test_num,cov_size);
      for i=1:test_num,
          for j=1:cov_size,
              K_test(i,j) = exp(-norm(A1(i,:)-A1(j,:))^2/rbf_var);
          end
      end
      K_test_n = K_test - unit_test*K - K_test*unit + unit_test*K*unit;
      test_features = zeros(test_num, max_ev);
      test_features = K_test_n * evecs(:,1:max_ev);
      A2=test_features;


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
      test_num=size(C1,1);
      unit_test = ones(test_num,cov_size)/cov_size;
      K_test = zeros(test_num,cov_size);
      for i=1:test_num,
          for j=1:cov_size,
              K_test(i,j) = exp(-norm(C1(i,:)-A1(j,:))^2/rbf_var);
          end
      end
      K_test_n = K_test - unit_test*K - K_test*unit + unit_test*K*unit;
      test_features = zeros(test_num, max_ev);
      test_features = K_test_n * evecs(:,1:max_ev);
      C2=test_features;


      model = svmtrain(B1, A2, '-s 3 -t 2 -g 1 -c 100 -p 1.5');
      [y, accuracy] = svmpredict(B1, C2, model);
      toc
      t=toc;