Hellinger Sciencia

Hellinger Distance is a mathematical way to measure how different two probability distributions are. Think of it as a "distance" that quantifies the similarity between two sets of possible outcomes, such as different patterns in data. A Hellinger distance of zero means the distributions are identical, while a larger value indicates they are more different. It’s useful in statistics and machine learning for comparing models, testing data differences, or blending data sources, providing a sensitive measure of the divergence between two probability scenarios.