SED

SED, or Standardized Euclidean Distance, is a way to measure how similar or different two data points are, taking into account the importance of each feature. Imagine comparing two objects based on multiple characteristics—SED calculates the differences for each feature, scales them by how much variation there is in each feature across all data, and then combines these into a single number. A smaller SED indicates the objects are more similar, while a larger SED shows greater differences. It’s commonly used in data analysis and pattern recognition to quantify similarity between data points.