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ROC Curve
Author:
Victor Hui
Topic:
Statistics
Receiver Operating Characteristic Curve
Correspondence between score distributions and the ROC curve (
https://en.wikipedia.org/wiki/Receiver_operating_characteristic
)
d (x-axis) is the score returned by a binary classifier
The red and blue hatchings are distributions of the scores of the positive and negative truths
Let the distributions be normal, move "
<-->
" to adjust the location and scale
d* is a threshold setting to separate the mixing of the positive and negative classifications
The blue shaded region (d < d*) is the distribution of false positive (FP) scores
The red shaded region (d > d*) is the distribution of false negative (FN) scores
The area of the blue shaded region yields the false positive rate FPR
The area of the red hatching less the area of the red shade yields the truth positive rate TPR
The ROC curve is the plot of TPR vs FPR as function of the threshold setting d*
Move d* on Graph to trace the ROC curve on Graph2
Question
:
Find an optimal threshold setting
d*
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