Finding the members in a confusion matrix I have inferred a confusion matrix of training and test set by neural network. I want to know which members are in the confusion matrix.

&gt; table(test$TRG,predicted.nn.values$net.result)

    0 1
  0 5 4
  1 5 3
&gt; 

&gt; head(train[,1:4])
  TRG      ALB     AQP9   CALML5
1   1 5.865827 8.190945 6.705303
2   1 6.998435 8.424261 8.505591
3   1 7.424512 8.716471 7.249556
4   1 7.442049 8.325263 8.809286
6   1 5.893411 8.199990 6.677618
7   1 7.288030 9.143510 7.088598
&gt; 

&gt; head(test[,1:4])
   TRG      ALB     AQP9    CALML5
5    1 6.369307 7.954310  6.920290
8    1 6.181902 8.651442  7.225389
10   1 6.119359 9.345270  6.829623
13   1 7.775533 9.016272  7.976813
14   1 5.913656 9.484457 10.609013
18   1 6.603138 7.908560  8.827173
&gt; 


How can I know which patients are false positive or true negative? For example I have 5 patients predicted correctly, how can I know the name of these patients?
This does not look a great confusion matrix, but it is a very, very cool approach. The cool thing about machine learning is the ability to examine lots of models within confusion matrices.



To answer your question, you want a heat map of the regression weights to establish who is who, i.e. which patient is false positive etc... This is the only way I'm aware of to analyse a neural network. This looks like R, I only know Scikit learn.