i want to calculate precision , recall , f-score and ...., but i get this erro:
Undefined function 'diag' for input arguments of type 'mlearnlib.graphics.chart.ConfusionMatrixChart'.
Error in SHIVANaugmented (line 74)
tp_m = diag(cm);
==============================================the following is a part of my code:
cm=confusionchart (imdsValidation.Labels, YPred);
%%
tp_m = diag(cm);
for i = 1:2 % number of classes
TP = tp_m(i);
FP = sum(cm(:, i), 1) - TP;
FN = sum(cm(i, :), 2) - TP;
TN = sum(cm(:)) - TP - FP - FN;
Accuracy = (TP+TN)./(TP+FP+TN+FN);
TPR = TP./(TP + FN);%tp/actual positive RECALL SENSITIVITY
if isnan(TPR)
TPR = 0;
end
PPV = TP./ (TP + FP); % tp / predicted positive PRECISION
if isnan(PPV)
PPV = 0;
end
TNR = TN./ (TN+FP); %tn/ actual negative SPECIFICITY
if isnan(TNR)
TNR = 0;
end
FPR = FP./ (TN+FP);
if isnan(FPR)
FPR = 0;
end
FScore = (2*(PPV * TPR)) / (PPV+TPR);
if isnan(FScore)
FScore = 0;
end
end
%%
save youRnetwork net

2 Comments

A confusion chart is a graphic object. What are you hoping that diag() of one would return?
Number

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 Accepted Answer

tp_m = diag(cm.NormalizedValues);

5 Comments

excuse me i get this error:
Error using sum
Invalid data type. First argument must be numeric or logical.
Error in SHIVANaugmented (line 78)
FP = sum(cm(:, i), 1) - TP;
Well, Don't Do That.
The return value from confusionchart is not a confusion matrix !!
yes i read it but i can not fix my error
Go back to your original code and change
cm=confusionchart (imdsValidation.Labels, YPred);
to
cc = confusionchart (imdsValidation.Labels, YPred);
cm = cc.NormalizedValues;
excellent it is working now. thank you

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