Given a confusion matrix as input, this function calculates the main statistics of interest (including macro AVG and microAVG):
'name' 'classes' 'macroAVG' 'microAVG'
Precision / / / x o
Specificity / / / x o
Sensitivity / / / x o
Accuracy / / / x o
F1-score / / / x o
Eugenio Bertolini (2021). Precision, Specificity, Sensitivity, Accuracy & F1-score (https://www.mathworks.com/matlabcentral/fileexchange/86158-precision-specificity-sensitivity-accuracy-f1-score), MATLAB Central File Exchange. Retrieved .
I believe that your function has mixed up false positives and false negatives in the confusion matrix output by confusionmat(). See for example the output by built-in functions plotconfusion() and confusionchart().
One simple fix would be to do:
at the beginning of statsOfMeasure()
Excellent tool. Great work!
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