Daniel Voigt Godoy - Deep Learning with PyTorch Step-by-Step A Beginner’s Guide-leanpub

Figure 3.13 - Using a low threshold
You can see in the figure above that lowering the threshold (moving it to the left
on the probability line) turned one false negative into a true positive (blue point
close to 0.4), but it also turned one true negative into a false positive (red point
close to 0.4).
Let’s double-check it with Scikit-Learn’s confusion matrix:
confusion_matrix(y_val, (probabilities_val >= 0.3))
Output
array([[ 6, 3],
[ 0, 11]])
OK, now let’s plot the corresponding metrics one more time:
Figure 3.14 - Trade-offs for two different thresholds
Still not a curve, I know, but we can already learn something from these two points.
Classification Threshold | 251