I computed confusion matrix in matlab and ı have 62 classes and give examples of my results 1, 2, 3 ,4, 5 ..etc can anybody help me about this subject please.
Hi
ROC curves are thought for binary problems by definition, since you have to plot the True Positive Fraction (TPF) or also called sensibility versus the False Positive Fraction (FPF) or 1-specificity
In the case of knn, for example, if you have only two classes and you use 62 neighbours (62-nn) the output of your classifier is the number of postiive samples among the 62 nearest neighbours.
In Matlab for example you can find information here:
http://es.mathworks.com/help/stats/perfcurve.html
The function perfcurve must receive:
A vector called labels that contains the label of every sample (values 0 or 1 because it is a binary classification problem).
A vector called scores that is the output of the 62-nn (the number of positive samples among the 62 nearest neighbours).
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