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  2. Centroid - Wikipedia

    en.wikipedia.org/wiki/Centroid

    Centroid of a triangle. In mathematics and physics, the centroid, also known as geometric center or center of figure, of a plane figure or solid figure is the arithmetic mean position of all the points in the surface of the figure. [further explanation needed] The same definition extends to any object in -dimensional Euclidean space. [1]

  3. List of centroids - Wikipedia

    en.wikipedia.org/wiki/List_of_centroids

    The following is a list of centroids of various two-dimensional and three-dimensional objects. The centroid of an object X {\displaystyle X} in n {\displaystyle n} - dimensional space is the intersection of all hyperplanes that divide X {\displaystyle X} into two parts of equal moment about the hyperplane.

  4. Pappus's centroid theorem - Wikipedia

    en.wikipedia.org/wiki/Pappus's_centroid_theorem

    The theorem applied to an open cylinder, cone and a sphere to obtain their surface areas. The centroids are at a distance a (in red) from the axis of rotation.. In mathematics, Pappus's centroid theorem (also known as the Guldinus theorem, Pappus–Guldinus theorem or Pappus's theorem) is either of two related theorems dealing with the surface areas and volumes of surfaces and solids of ...

  5. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    A typical example of the k-means convergence to a local minimum. In this example, the result of k-means clustering (the right figure) contradicts the obvious cluster structure of the data set. The small circles are the data points, the four ray stars are the centroids (means).

  6. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Centroid-based clustering problems such as k-means and k-medoids are special cases of the uncapacitated, metric facility location problem, a canonical problem in the operations research and computational geometry communities. In a basic facility location problem (of which there are numerous variants that model more elaborate settings), the task ...

  7. Lloyd's algorithm - Wikipedia

    en.wikipedia.org/wiki/Lloyd's_algorithm

    Like the closely related k-means clustering algorithm, it repeatedly finds the centroid of each set in the partition and then re-partitions the input according to which of these centroids is closest. In this setting, the mean operation is an integral over a region of space, and the nearest centroid operation results in Voronoi diagrams.

  8. k-medians clustering - Wikipedia

    en.wikipedia.org/wiki/K-medians_clustering

    This relates directly to the k-median problem which is the problem of finding k centers such that the clusters formed by them are the most compact with respect to the 2-norm. Formally, given a set of data points x , the k centers c i are to be chosen so as to minimize the sum of the distances from each x to the nearest c i .

  9. Incenter - Wikipedia

    en.wikipedia.org/wiki/Incenter

    The incenter must lie in the interior of a disk whose diameter connects the centroid G and the orthocenter H (the orthocentroidal disk), but it cannot coincide with the nine-point center, whose position is fixed 1/4 of the way along the diameter (closer to G). Any other point within the orthocentroidal disk is the incenter of a unique triangle ...