MATLAB: How to display (show) the similarty of test image in neural network

Deep Learning Toolboximage processingneural network

hi every body…. i used neural network…i want when enter the test image the neural network display the most similarty image of test image…how can do that?? plz help me??
the code which used is :
        function taning2
  load dataset2;
      mynet = newff(P,T,50);
mynet.trainParam.epochs = 3000;
mynet.trainParam.goal        =1e-6;
      mynet.trainParam.lr          = 0.01;
      mynet.divideFcn = 'dividerand';  % Divide data randomly
  mynet.divideMode = 'sample';  % Divide up every sample
  mynet.divideParam.trainRatio = 70/100;
  mynet.divideParam.valRatio = 15/100;
  mynet.divideParam.testRatio = 15/100;
  mynet.trainParam.show        = 100;
  mynet.trainparam.mc          = 0.95;
   mynet.trainParam.max_fail       = 30;
      mynet.trainFcn = 'trainscg';
      mynet.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
    'plotregression', 'plotfit'};
% Train the Network
[mynet,tr] = train(mynet,P,T);
% Test the Network
outputs = mynet(P);
errors = gsubtract(T,outputs);
performance = perform(mynet,T,outputs);
      trainTargets = T.* tr.trainMask{1};
  valTargets = T  .* tr.valMask{1};
  testTargets = T  .* tr.testMask{1};
  trainPerformance = perform(mynet,trainTargets,outputs);
  valPerformance = perform(mynet,valTargets,outputs);
  testPerformance = perform(mynet,testTargets,outputs);
      save mynet
and the files which used to testenter image is :
      function testing2
load mynet;
load dataset2;
image_dims = [46, 64];
images2 = [];
num_images1=1;
m=imread('E:\matlab\project\neuralnetwork\a\img1.jpg');
if num_images1==1
     images2 = zeros(prod(image_dims), num_images1);
end
img2=imresize(m,[46, 64]); 
    images2(:,1) = img2(:);
%     mean_face = mean(images, 2);
    mean_face4 = mean(images2, 1);
     shifted_images2 = images2 - repmat(mean_face4, 1, num_images1 );
     [evectors1,score1,  evalues1] = pcacov(images2');
     num_eigenface1=16;
% % % % % % %      evectors3=evectors1;
evectors3 = evectors1(:, 1:num_eigenface1);
 score3(1,1)=score1(1,1);
 evalues3=evalues1';
  evalues4(1,1)= evalues3(1,1);
    features2 = evectors3' * shifted_images2;
  features4=features2' ;
  [features3,PS2] = mapminmax(features4);
  features3=features3';
  input=[features3;score3;evalues4];
  [input,PS2] = mapminmax(input');
  input=input';
%tt=[1 0;0 1];
% out=mynet11(input);
% figure,plotconfusion(T,out);
simpleclassOutputs2 = sim(mynet,input);
 class = vec2ind(simpleclassOutputs2);
 disp( class );
simpleclassOutputs2 = sim(mynet,input);
 figure,plotconfusion(simpleclassOutputs2,T);

Best Answer

I cannot find a MATLAB code for a nearest-neighbor classifier. It looks like you'll have to code your own.
Looking at the source code of NEWPNN might help.
Greg
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