- Here is the code for the network. *

`%%%%%%%%%%%%%%%%%%%%%%%Code %%%%%%%%%%%%%%%%%%%%%%%%`

% train_input -- 224 * 320 matrix containing 80 samples each with 224 features

% test_input -- 224 * 80 matrix containing 80 samples each with 224 features

% train_target -- 40 * 320 containing 320 samples

% test_target -- 40 * 80 containing 80 samples

setdemorandstream(491218382); net = patternnet(44); net.performFcn = 'mse'; net.trainFcn = 'trainscg'; net.layers{1}.transferFcn = 'tansig'; net.layers{2}.transferFcn = 'tansig'; net.divideParam.trainRatio = 1.0; % training set [%]

net.divideParam.valRatio = 0.0; % validation set [%]

net.divideParam.testRatio = 0.0; % test set [%]

net.trainParam.epochs = 300; net.trainParam.showWindow = 0; [net,tr] = train(net,train_input,train_target)%%%%%%%%%%%%%%%%%%%%Inbuilt Testing of the Network %%%%%%%%%%%%%%%%%%%%%%%%

testY = net(test_input); [c,cm] = confusion(test_target,testY); fprintf('Percentage Correct Classification : %f%%\n', 100*(1-c)); %%%%%%Output : Percentage Correct Classification : 95 % %%%%%%

%%%%%%%%%%%%%%%%%%%Custom Designed Testing of the Network %%%%%%%%%%%%%%%%%%%

wb = formwb(net,net.b,net.iw,net.lw); [b,iw,lw] = separatewb(net,wb); weight_input = iw{1,1}; weight_hidden = lw{2,1}; bias_input = b{1,1}; bias_hidden = b{2,1}; test_input = mapminmax(test_input); test_input = removeconstantrows(test_input); hidden = []; output = []; indx = []; for j = 1:80 %%%%%%1st Layer Calculation %%%%%

for k = 1:44 weighted_sum = sum(times(test_input(:,j),weight_input(k,:)')); hidden(k,j) = 2/(1+exp(-2*(weighted_sum + bias_input(k))))-1; %%%Tansig Function

end %%%%%%2nd Layer Calculation %%%%%

for k = 1:40 weighted_sum = sum(times(hidden(:,j),weight_hidden(k,:)')); output(k,j) = 2/(1+exp(-2*(weighted_sum + bias_hidden(k))))-1; %%%Tansig Function end output = mapminmax(output); [c,cm] = confusion(test_target,output); fprintf('Percentage Correct Classification : %f%%\n', 100*(1-c)); %%%%%%Output : Percentage Correct Classification : 90 % %%%%%%

Why is there a difference in percentage of correct classification when both are expected to be equal?

## Best Answer