I have a code of multiplayer perceptron , which i have modified for 10 cross validation. but the confusion matrix in final display is not understandable. can someone please

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ammu v
ammu v on 31 Jul 2021
Edited: ammu v on 3 Aug 2021
%% i have 184 subjects, i cant decipher the confusiion matrix
feat = classi_tau4_norm(:,1:16);
labels = classi_tau4_norm(:,17)
fold = cvpartition(labels,'kfold',10);
net = patternnet(6);
while r<=10
trainIdx=fold.training(r); testIdx=fold.test(r);
xtrain=feat(trainIdx,:); ytrain=labels(trainIdx);
xtest = feat(testIdx,:); ytest = labels(testIdx);
train_data=[ytrain xtrain];
test_data = [ytest xtest];
net = train(net,xtrain',ytrain');
y_pred = net(xtest');
perf = perform(net,ytest,y_pred');

Answers (1)

Amogh Bhole
Amogh Bhole on 3 Aug 2021
From my understanding the confusion matrix you obtained is a result of binary classification problem. Also, I am not able to find where you are plotting the confusion matrix in the code provided. I can see from the image that you have obtained four confusion matrices. However, these confusion matrices mean as follows:
  1. Training Confusion Matrix: This matrix gives the information on the data used during training it will be on the random nine folds.
  2. Validation Confusion Matrix: Since you are using cross validation technique, the matrix is obtained on the random tenth fold which is used for validation during training.
  3. Test Confusion Matrix: For each iteration it will give the confusion matrix for the testing data used.
  4. All Confusion Matrix: For each iteration it will give the combined information of the above three matrices.
Please refer to this link in order to find more ways to plot the confusion matrix.
  1 Comment
ammu v
ammu v on 3 Aug 2021
i didnt write any code for generating confusion matrix, it was generating automatically. I wanted to obtain a proper confusion matrix with total TP,TN,FP,FN.However i am unable to extract with this code.

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