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  2. Ranking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Ranking_(statistics)

    In statistics, ranking is the data transformation in which numerical or ordinal values are replaced by their rank when the data are sorted. For example, if the numerical data 3.4, 5.1, 2.6, 7.3 are observed, the ranks of these data items would be 2, 3, 1 and 4 respectively.

  3. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some specific sense defined by the analyst) to each other than to those in other groups (clusters).

  4. Model-based clustering - Wikipedia

    en.wikipedia.org/wiki/Model-based_clustering

    These arise when individuals rank objects in order of preference. The data are then ordered lists of objects, arising in voting, education, marketing and other areas. Model-based clustering methods for rank data include mixtures of Plackett-Luce models and mixtures of Benter models, [29] [30] and mixtures of Mallows models. [31]

  5. Production flow analysis - Wikipedia

    en.wikipedia.org/wiki/Production_flow_analysis

    Given a binary product-machines n-by-m matrix , rank order clustering [1] is an algorithm characterized by the following steps: . For each row i compute the number =; Order rows according to descending numbers previously computed

  6. 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

  7. Ordination (statistics) - Wikipedia

    en.wikipedia.org/wiki/Ordination_(statistics)

    Ordination or gradient analysis, in multivariate analysis, is a method complementary to data clustering, and used mainly in exploratory data analysis (rather than in hypothesis testing). In contrast to cluster analysis, ordination orders quantities in a (usually lower-dimensional) latent space. In the ordination space, quantities that are near ...

  8. Order statistic - Wikipedia

    en.wikipedia.org/wiki/Order_statistic

    Order statistics have a lot of applications in areas as reliability theory, financial mathematics, survival analysis, epidemiology, sports, quality control, actuarial risk, etc. There is an extensive literature devoted to studies on applications of order statistics in these fields.

  9. Learning to rank - Wikipedia

    en.wikipedia.org/wiki/Learning_to_rank

    Learning to rank algorithms have been applied in areas other than information retrieval: In machine translation for ranking a set of hypothesized translations; [8]; In computational biology for ranking candidate 3-D structures in protein structure prediction problems; [8]