enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. WPGMA - Wikipedia

    en.wikipedia.org/wiki/WPGMA

    At each step, the nearest two clusters, say and , are combined into a higher-level cluster . Then, its distance to another cluster k {\displaystyle k} is simply the arithmetic mean of the average distances between members of k {\displaystyle k} and i {\displaystyle i} and k {\displaystyle k} and j {\displaystyle j} :

  3. Automatic clustering algorithms - Wikipedia

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

    Automatic clustering algorithms are algorithms that can perform clustering without prior knowledge of data sets. In contrast with other cluster analysis techniques, automatic clustering algorithms can determine the optimal number of clusters even in the presence of noise and outlier points. [1] [needs context]

  4. UPGMA - Wikipedia

    en.wikipedia.org/wiki/UPGMA

    At each step, the nearest two clusters are combined into a higher-level cluster. The distance between any two clusters and , each of size (i.e., cardinality) | | and | |, is taken to be the average of all distances (,) between pairs of objects in and in , that is, the mean distance between elements of each cluster:

  5. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Download QR code; Print/export ... Cluster analysis or clustering is the task of grouping ... add the cell in the cluster and repeat steps 4.2 and 4.3 till there is ...

  6. 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]

  7. Biclustering - Wikipedia

    en.wikipedia.org/wiki/Biclustering

    Biclustering, block clustering, [1] [2] Co-clustering or two-mode clustering [3] [4] [5] is a data mining technique which allows simultaneous clustering of the rows and columns of a matrix. The term was first introduced by Boris Mirkin [ 6 ] to name a technique introduced many years earlier, [ 6 ] in 1972, by John A. Hartigan .

  8. Nearest-neighbor chain algorithm - Wikipedia

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

    In the theory of cluster analysis, the nearest-neighbor chain algorithm is an algorithm that can speed up several methods for agglomerative hierarchical clustering.These are methods that take a collection of points as input, and create a hierarchy of clusters of points by repeatedly merging pairs of smaller clusters to form larger clusters.

  9. Complete-linkage clustering - Wikipedia

    en.wikipedia.org/wiki/Complete-linkage_clustering

    In complete-linkage clustering, the link between two clusters contains all element pairs, and the distance between clusters equals the distance between those two elements (one in each cluster) that are farthest away from each other. The shortest of these links that remains at any step causes the fusion of the two clusters whose elements are ...