Distance methods

Distance methods measure how different or similar data points are based on specific calculations. Think of them as ways to quantify the "closeness" between items, such as customers or documents. For example, the Euclidean distance is like measuring the straight-line gap between two points in space. These methods are used in clustering, pattern recognition, and machine learning to group similar items or identify outliers. Essentially, distance methods provide a mathematical way to compare data and understand relationships within complex datasets.