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

It looks like this:
Figure 3.10 - Split probability line
"Why is it more visually interesting?" you ask.
Well, now all correctly classified and all misclassified points are in different
quadrants. There is something else that looks exactly like this…
Confusion Matrix
Those quadrants have names: true negative (TN) and false positive (FP), above the
line, false negative (FN) and true positive (TP), below the line.
Figure 3.11 - Probability line as a confusion matrix
Points above the line are actual negatives, points below the line are actual
positives.
Points to the right of the threshold are classified as positive, points to the left of
the threshold are classified as negative.
Cool, right? Let’s double-check it with Scikit-Learn’s confusion_matrix() method:
cm_thresh50 = confusion_matrix(y_val, (probabilities_val >= 0.5))
cm_thresh50
Classification Threshold | 243