F-divergence

F-divergence is a way to measure how different two things are. It is used to compare data sets, or to compare probability distributions.

To explain it in simple terms, think of two bowls of popcorn. You can measure how different they are by counting the number of kernels in each bowl - the bowl with more kernels has more popcorn, and is different from the other bowl. In the same way, F-divergence is a way to compare two groups of data or two probability distributions, and see how much they are different from each other.