![]() Its solution is now known as the Fermat point of the triangle formed by the three sample points. The special case of the problem for three points in the plane (that is, m = 3 and n = 2 in the definition below) is sometimes also known as Fermat's problem it arises in the construction of minimal Steiner trees, and was originally posed as a problem by Pierre de Fermat and solved by Evangelista Torricelli. If the point is generalized into a line or a curve, the best-fitting solution is found via least absolute deviations. The more general k-median problem asks for the location of k cluster centers minimizing the sum of distances from each sample point to its nearest center. It is also a standard problem in facility location, where it models the problem of locating a facility to minimize the cost of transportation. The geometric median is an important estimator of location in statistics, where it is also known as the L 1 estimator (after the L 1 norm). It is also known as the 1-median, spatial median, Euclidean minisum point, or Torricelli point. This generalizes the median, which has the property of minimizing the sum of distances for one-dimensional data, and provides a central tendency in higher dimensions. In geometry, the geometric median of a discrete set of sample points in a Euclidean space is the point minimizing the sum of distances to the sample points. ![]() Example of geometric median (in yellow) of a series of points. Not to be confused with Median (geometry) or Geometric mean. ![]()
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