Divergence measures

Divergence measures are mathematical tools used to quantify how different two probability distributions are from each other. Imagine having two sets of predictions or observations—divergence tells us how much they differ. For example, comparing expected outcomes to actual results or assessing how one model's predictions differ from another's. These measures help in understanding the discrepancy or deviation between datasets, models, or distributions, guiding improvements and decisions in statistics, machine learning, and data analysis.