Binary Classification _ problem with data structure

2 views (last 30 days)
Hi, i want to create neural network for binary classification so when i read in matlab doc for patternet that Classification problems involving only two classes can be represented using either format. The targets can consist of either scalar 1/0 elements or two-element vectors, with one element being 1 and the other element being 0.(link= https://www.mathworks.com/help/nnet/gs/classify-patterns-with-a-neural-network.html) so i tried to set each scalar target value to either 0 or 1 but in the confusion matrix i got NAN values for the second class
[ I N ] = [ 9 981 ]
[ O N ] = [ 1 981 ]
And this is the code
rng('default');
x = patientInputs;
t = patientTargets ;
trainFcn = 'trainscg'; % Scaled conjugate gradient backpropagation.
% Create a Pattern Recognition Network
hiddenLayerSize =10;
net = patternnet(hiddenLayerSize);
net.inputs{1}.processFcns = {'removeconstantrows','mapminmax'};
net.outputs{2}.processFcns = {'removeconstantrows','mapminmax'};
net.divideFcn = 'dividerand'; % Divide data randomly
net.divideMode = 'sample'; % Divide up every sample
net.divideParam.trainRatio = 70/100;
net.divideParam.valRatio = 15/100;
net.divideParam.testRatio = 15/100;
net.performFcn = 'mse'; % Cross-Entropy
% Choose Plot Functions
% For a list of all plot functions type: help nnplot
net.plotFcns = {'plotperform','plottrainstate','ploterrhist', ...
'plotconfusion', 'plotroc'};
% Train the Network
net= configure(net,x,t);
[net,tr] = train(net,x,t);
y = net(x);
e = gsubtract(t,y);
performance = perform(net,t,y)
tind = vec2ind(t);
yind = vec2ind(y);
percentErrors = sum(tind ~= yind)/numel(tind);
% Recalculate Training, Validation and Test Performance
trainTargets = t .* tr.trainMask{1};
valTargets = t .* tr.valMask{1};
testTargets = t .* tr.testMask{1};
trainPerformance = perform(net,trainTargets,y)
valPerformance = perform(net,valTargets,y)
testPerformance = perform(net,testTargets,y)
% View the Network
view(net)
i don't know why? can anyone tell me please?

Accepted Answer

Greg Heath
Greg Heath on 28 Jun 2017
There might be a caveat in the confusion matrix code that only accepts {0,1} 1-d outputs.
check it out.
Greg
  2 Comments
afef
afef on 28 Jun 2017
And i want to know when you said 1-d outputs. 'd' referes to what ??

Sign in to comment.

More Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by