When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Lloyd's algorithm - Wikipedia

    en.wikipedia.org/wiki/Lloyd's_algorithm

    Lloyd's algorithm is usually used in a Euclidean space. The Euclidean distance plays two roles in the algorithm: it is used to define the Voronoi cells, but it also corresponds to the choice of the centroid as the representative point of each cell, since the centroid is the point that minimizes the average squared Euclidean distance to the ...

  3. 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 ...

  4. Euclidean distance - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance

    It can be extended to infinite-dimensional vector spaces as the L 2 norm or L 2 distance. [25] The Euclidean distance gives Euclidean space the structure of a topological space, the Euclidean topology, with the open balls (subsets of points at less than a given distance from a given point) as its neighborhoods. [26]

  5. Euclidean distance matrix - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance_matrix

    In mathematics, a Euclidean distance matrix is an n×n matrix representing the spacing of a set of n points in Euclidean space. For points x 1 , x 2 , … , x n {\displaystyle x_{1},x_{2},\ldots ,x_{n}} in k -dimensional space ℝ k , the elements of their Euclidean distance matrix A are given by squares of distances between them.

  6. Mean line segment length - Wikipedia

    en.wikipedia.org/wiki/Mean_line_segment_length

    In other words, it is the expected Euclidean distance between two random points, where each point in the shape is equally likely to be chosen. Even for simple shapes such as a square or a triangle, solving for the exact value of their mean line segment lengths can be difficult because their closed-form expressions can get quite complicated. As ...

  7. Multidimensional scaling - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_scaling

    In classical MDS, this norm is the Euclidean distance, but, in a broader sense, it may be a metric or arbitrary distance function. [6] For example, when dealing with mixed-type data that contain numerical as well as categorical descriptors, Gower's distance is a common alternative. [citation needed]

  8. Distance from a point to a plane - Wikipedia

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

    In Euclidean space, the distance from a point to a plane is the distance between a given point and its orthogonal projection on the plane, ...

  9. Weighted Voronoi diagram - Wikipedia

    en.wikipedia.org/wiki/Weighted_Voronoi_diagram

    In a multiplicatively weighted Voronoi diagram, the distance between a point and a site is divided by the (positive) weight of the site. [1] In the plane under the ordinary Euclidean distance, the multiplicatively weighted Voronoi diagram is also called circular Dirichlet tessellation [2] [3] and its edges are circular arcs and straight line ...