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  2. Ranking SVM - Wikipedia

    en.wikipedia.org/wiki/Ranking_SVM

    Suppose is a data set containing elements . is a ranking method applied to .Then the in can be represented as a binary matrix. If the rank of is higher than the rank of , i.e. < , the corresponding position of this matrix is set to value of "1".

  3. Kruskal–Wallis test - Wikipedia

    en.wikipedia.org/wiki/Kruskal–Wallis_test

    The Kruskal–Wallis test by ranks, Kruskal–Wallis test (named after William Kruskal and W. Allen Wallis), or one-way ANOVA on ranks is a non-parametric statistical test for testing whether samples originate from the same distribution. [1] [2] [3] It is used for comparing two or more independent samples of equal or different sample sizes.

  4. Quantile normalization - Wikipedia

    en.wikipedia.org/wiki/Quantile_normalization

    In the case of column 2, they represent ranks iii and iv. So we assign the two tied rank iii entries the average of rank iii and rank iv ((4.67 + 5.67)/2 = 5.17). And so we arrive at the following set of normalized values:

  5. ANOVA on ranks - Wikipedia

    en.wikipedia.org/wiki/ANOVA_on_ranks

    Conover and Iman provided a review of the four main types of rank transformations (RT). [1] One method replaces each original data value by its rank (from 1 for the smallest to N for the largest). This rank-based procedure has been recommended as being robust to non-normal errors, resistant to outliers, and highly efficient for many distributions.

  6. Jonckheere's trend test - Wikipedia

    en.wikipedia.org/wiki/Jonckheere's_Trend_Test

    This may be verified by substituting 11 mph in place of 12 mph in the Bumped sample, and 19 mph in place of 20 mph in the Smashed and re-computing the test statistic. From tables with k = 3, and m = 4, the critical S value for α = 0.05 is 36 and thus the result would be declared statistically significant at this level.

  7. Ranking - Wikipedia

    en.wikipedia.org/wiki/Ranking

    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. 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.

  8. Friedman test - Wikipedia

    en.wikipedia.org/wiki/Friedman_test

    The Friedman test is a non-parametric statistical test developed by Milton Friedman. [1] [2] [3] Similar to the parametric repeated measures ANOVA, it is used to detect differences in treatments across multiple test attempts.

  9. Rank of an elliptic curve - Wikipedia

    en.wikipedia.org/wiki/Rank_of_an_elliptic_curve

    In Binary quartic forms having bounded invariants, and the boundedness of the average rank of elliptic curves, [7] Bhargava and Shankar computed the 2-Selmer rank of elliptic curves on average. They did so by counting binary quartic forms , using a method used by Birch and Swinnerton-Dyer in their original computation of the analytic rank of ...