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  2. Hierarchical clustering - Wikipedia

    en.wikipedia.org/wiki/Hierarchical_clustering

    The standard algorithm for hierarchical agglomerative clustering (HAC) has a time complexity of () and requires () memory, which makes it too slow for even medium data sets. . However, for some special cases, optimal efficient agglomerative methods (of complexity ()) are known: SLINK [2] for single-linkage and CLINK [3] for complete-linkage clusteri

  3. Ward's method - Wikipedia

    en.wikipedia.org/wiki/Ward's_method

    In statistics, Ward's method is a criterion applied in hierarchical cluster analysis. Ward's minimum variance method is a special case of the objective function approach originally presented by Joe H. Ward, Jr. [ 1 ] Ward suggested a general agglomerative hierarchical clustering procedure, where the criterion for choosing the pair of clusters ...

  4. UPGMA - Wikipedia

    en.wikipedia.org/wiki/UPGMA

    UPGMA (unweighted pair group method with arithmetic mean) is a simple agglomerative (bottom-up) hierarchical clustering method. It also has a weighted variant, WPGMA, and they are generally attributed to Sokal and Michener.

  5. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis is for example used to identify groups of schools or students with similar properties. Typologies From poll data, projects such as those undertaken by the Pew Research Center use cluster analysis to discern typologies of opinions, habits, and demographics that may be useful in politics and marketing.

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

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

    In statistics and data mining, X-means clustering is a variation of k-means clustering that refines cluster assignments by repeatedly attempting subdivision, and keeping the best resulting splits, until a criterion such as the Akaike information criterion (AIC) or Bayesian information criterion (BIC) is reached.

  7. Complete-linkage clustering - Wikipedia

    en.wikipedia.org/wiki/Complete-linkage_clustering

    Complete-linkage clustering is one of several methods of agglomerative hierarchical clustering. At the beginning of the process, each element is in a cluster of its own. The clusters are then sequentially combined into larger clusters until all elements end up being in the same cluster. The method is also known as farthest neighbour clustering.

  8. Single-linkage clustering - Wikipedia

    en.wikipedia.org/wiki/Single-linkage_clustering

    In statistics, single-linkage clustering is one of several methods of hierarchical clustering.It is based on grouping clusters in bottom-up fashion (agglomerative clustering), at each step combining two clusters that contain the closest pair of elements not yet belonging to the same cluster as each other.

  9. WPGMA - Wikipedia

    en.wikipedia.org/wiki/WPGMA

    WPGMA (Weighted Pair Group Method with Arithmetic Mean) is a simple agglomerative (bottom-up) hierarchical clustering method, generally attributed to Sokal and Michener. [ 1 ] The WPGMA method is similar to its unweighted variant, the UPGMA method.