Classifier Calibration: with application to threat scores in cybersecurity. (arXiv:2102.05143v3 [cs.LG] UPDATED)

This paper explores the calibration of a classifier output score in binary
classification problems. A calibrator is a function that maps the arbitrary
classifier score, of a testing observation, onto $[0,1]$ to provide an estimate
for the posterior probability of belonging to one of the two classes.
Calibration is important for two reasons; first, it provides a meaningful
score, that is the posterior probability; second, it puts the scores of
different classifiers on the same scale for comparable interpretation. The …

application cybersecurity lg threat