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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. 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

  4. Cluster analysis - Wikipedia

    en.wikipedia.org/wiki/Cluster_analysis

    Cluster analysis has been used to cluster stocks into sectors. [64] Petroleum geology Cluster analysis is used to reconstruct missing bottom hole core data or missing log curves in order to evaluate reservoir properties. Geochemistry The clustering of chemical properties in different sample locations.

  5. Order statistic - Wikipedia

    en.wikipedia.org/wiki/Order_statistic

    Together with rank statistics, order statistics are among the most fundamental tools in non-parametric statistics and inference. Important special cases of the order statistics are the minimum and maximum value of a sample, and (with some qualifications discussed below) the sample median and other sample quantiles.

  6. 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]

  7. Ranking - Wikipedia

    en.wikipedia.org/wiki/Ranking

    As another example, the ordinal data hot, cold, warm would be replaced by 3, 1, 2. In these examples, the ranks are assigned to values in ascending order, although descending ranks can also be used. Ranks are related to the indexed list of order statistics, which consists of the original dataset rearranged into ascending order.

  8. Learning to rank - Wikipedia

    en.wikipedia.org/wiki/Learning_to_rank

    Learning to rank [1] or machine-learned ranking (MLR) is the application of machine learning, typically supervised, semi-supervised or reinforcement learning, in the construction of ranking models for information retrieval systems. [2] Training data may, for example, consist of lists of items with some partial order specified between items in ...

  9. Rank correlation - Wikipedia

    en.wikipedia.org/wiki/Rank_correlation

    Dave Kerby (2014) recommended the rank-biserial as the measure to introduce students to rank correlation, because the general logic can be explained at an introductory level. The rank-biserial is the correlation used with the Mann–Whitney U test, a method commonly covered in introductory college courses on statistics. The data for this test ...