What is the Euclidean Distance?

The Euclidean Distance is a measure of the distance between two points in a Euclidean space. It is calculated by taking the square root of the sum of the squared differences between the coordinates of the two points. For example, if two points have coordinates (x1, y1) and (x2, y2), then the Euclidean Distance between them is given by:

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

The Euclidean Distance is a useful measure for many applications, such as clustering, classification, and regression. It is also used in machine learning algorithms such as k-means clustering and k-nearest neighbors.

Next Chapter:

What is the Jaccard Similarity?

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