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  2. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    For pairs of objects that are not both points, the distance can most simply be defined as the smallest distance between any two points from the two objects, although more complicated generalizations from points to sets such as Hausdorff distance are also commonly used. [6] Formulas for computing distances between different types of objects include:

  3. Distance - Wikipedia

    en.wikipedia.org/wiki/Distance

    The distance travelled by an object is the length of a specific path travelled between two points, [6] such as the distance walked while navigating a maze. This can even be a closed distance along a closed curve which starts and ends at the same point, such as a ball thrown straight up, or the Earth when it completes one orbit .

  4. Chebyshev distance - Wikipedia

    en.wikipedia.org/wiki/Chebyshev_distance

    The two dimensional Manhattan distance has "circles" i.e. level sets in the form of squares, with sides of length √ 2 r, oriented at an angle of π/4 (45°) to the coordinate axes, so the planar Chebyshev distance can be viewed as equivalent by rotation and scaling to (i.e. a linear transformation of) the planar Manhattan distance.

  5. Closest pair of points problem - Wikipedia

    en.wikipedia.org/wiki/Closest_pair_of_points_problem

    The closest pair of points problem or closest pair problem is a problem of computational geometry: given points in metric space, find a pair of points with the smallest distance between them. The closest pair problem for points in the Euclidean plane [ 1 ] was among the first geometric problems that were treated at the origins of the systematic ...

  6. Signed distance function - Wikipedia

    en.wikipedia.org/wiki/Signed_distance_function

    In mathematics and its applications, the signed distance function or signed distance field (SDF) is the orthogonal distance of a given point x to the boundary of a set Ω in a metric space (such as the surface of a geometric shape), with the sign determined by whether or not x is in the interior of Ω.

  7. Similarity measure - Wikipedia

    en.wikipedia.org/wiki/Similarity_measure

    Manhattan distance is commonly used in GPS applications, as it can be used to find the shortest route between two addresses. [citation needed] When you generalize the Euclidean distance formula and Manhattan distance formula you are left with the Minkowski distance formulas, which can be used in a wide variety of applications. Euclidean distance

  8. Distance from a point to a line - Wikipedia

    en.wikipedia.org/wiki/Distance_from_a_point_to_a...

    The distance (or perpendicular distance) from a point to a line is the shortest distance from a fixed point to any point on a fixed infinite line in Euclidean geometry. It is the length of the line segment which joins the point to the line and is perpendicular to the line. The formula for calculating it can be derived and expressed in several ways.

  9. Medoid - Wikipedia

    en.wikipedia.org/wiki/Medoid

    This example shows how Euclidean distance will calculate the distance between objects to determine how similar the items are. Note that most text embeddings will be at least a few hundred dimensions instead of just two. Euclidean distance is a standard distance metric used to measure the dissimilarity between two points in a multi-dimensional ...