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  2. Automatic clustering algorithms - Wikipedia

    en.wikipedia.org/wiki/Automatic_Clustering...

    Therefore, the generated clusters from this type of algorithm will be the result of the distance between the analyzed objects. Hierarchical models can either be divisive, where partitions are built from the entire data set available, or agglomerating, where each partition begins with a single object and additional objects are added to the set ...

  3. Lists of clusters - Wikipedia

    en.wikipedia.org/wiki/Lists_of_clusters

    The following are lists of clusters: List of galaxy groups and clusters; List of open clusters; List of globular clusters; See also. List of superclusters

  4. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Mark cell ‘c’ as a new cluster; Calculate the density of all the neighbors of ‘c’ If the density of a neighboring cell is greater than threshold density then, add the cell in the cluster and repeat steps 4.2 and 4.3 till there is no neighbor with a density greater than threshold density. Repeat steps 2,3 and 4 till all the cells are ...

  5. Small cell - Wikipedia

    en.wikipedia.org/wiki/Small_cell

    Small-cell networks can also be realized by means of distributed radio technology using centralized baseband units and remote radio heads. Beamforming technology (focusing a radio signal on a very specific area) can further enhance or focus small cell coverage. These approaches to small cells all feature central management by mobile network ...

  6. List of cluster management software - Wikipedia

    en.wikipedia.org/wiki/List_of_cluster_management...

    Aspen Systems Inc - Aspen Cluster Management Environment (ACME) Borg, used at Google; Bright Cluster Manager, from Bright Computing; ClusterVisor, [2] from Advanced Clustering Technologies [3] CycleCloud, from Cycle Computing acquired By Microsoft; Komodor, Enterprise Kubernetes Management Platform; Dell/EMC - Remote Cluster Manager (RCM)

  7. Determining the number of clusters in a data set - Wikipedia

    en.wikipedia.org/wiki/Determining_the_number_of...

    The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]

  8. Hoshen–Kopelman algorithm - Wikipedia

    en.wikipedia.org/wiki/Hoshen–Kopelman_algorithm

    grid[4][3] is occupied so check cell to the left and above, both, cell to the left and above are occupied so merge the two clusters and assign the cluster label of the cell above to the cell on the left and to this cell i.e. 5. (Merging using union algorithm will label all the cells with label 6 to 5). grid[4][4] is unoccupied so it is not labeled.

  9. Nearest-neighbor chain algorithm - Wikipedia

    en.wikipedia.org/wiki/Nearest-neighbor_chain...

    Instead it is possible to maintain an array of distances between all pairs of clusters. Whenever two clusters are merged, the formula can be used to compute the distance between the merged cluster and all other clusters. Maintaining this array over the course of the clustering algorithm takes time and space O(n 2). The nearest-neighbor chain ...