L2-norm distance

The L2-norm distance, also known as the Euclidean distance, is a measure of the distance between two points in a Euclidean space. It calculates the straight-line distance between the two points.

In a two-dimensional space, the L2-norm distance between two points (x1, y1) and (x2, y2) can be calculated using the Pythagorean theorem:

distance = sqrt((x2 - x1)^2 + (y2 - y1)^2)

In a higher-dimensional space, the formula extends to:

distance = sqrt((x2 - x1)^2 + (y2 - y1)^2 + ... + (zn - z1)^2)

The L2-norm distance is commonly used in various fields, such as machine learning, data analysis, and computer vision, to measure the similarity or dissimilarity between data points.