I am playing with ROC and trying to draw some curves. I am using example from this scikit page. I do not understand one thing: when I print out the content of tpr and fpr, I see two arrays of numbers (21 elems in each) - why is that?
TPR (True Positive Ratio) is a proportion of those tuples classified as positives to all real positive tuples. So, it should be one number
I see it as follow: I take classifier (like Decision Tree), train it on some data and finally test it. Then I can calculate TPR and FPR and I should have only two values.
Instead, I receive arrays. Why is that? I tried to change classifier from that example to Decision Tree and then I receive only one point (which is usually [0, 1]). How can I draw ROC curve on decision tree? Or - to be more precise with my question - why do I get an array of values as my TRP/FPR instead of single values?