I want to plot ROC sensitivity vs specitivity,I have calcuated all these parameters for 3 class problem,now kindly tell how to plot roc crve
results are
Actual Classes
-------------1--------2--------3-----
TP | 38.00 | 50.00 | 50.00
FP | 12.00 | 0.00 | 0.00
FN | 0.00 | 12.00 | 0.00
TN | 100.00 | 88.00 | 100.00
Preci. | 0.76 | 1.00 | 1.00
Sensi. | 1.00 | 0.81 | 1.00
Speci. | 0.89 | 1.00 | 1.00
------------------------------------------
Model Accuracy is 0.92

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Star Strider
Star Strider 2014-11-15

0 个投票

Use the perfcurve function.

2 个评论

i tried this but could not plot it ,[x,y]=perfcurve();here i get x,y as only four values,where mu input to this function is 44 values
You have to give it the raw results of your classification, not the confusion matrix summary results you posted. I assume you have the classification results it requires. See the documentation on Performance Curves for a detailed discussion.
From that documentation:
  • perfcurve is intended for use with classifiers that return scores, not those that return only predicted classes. As a counter-example, consider a decision tree that returns only hard classification labels, 0 or 1, for data with two classes. In this case, the performance curve reduces to a single point because classified instances can be split into positive and negative categories in one way only.

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