Search results
Results from the WOW.Com Content Network
The ranking SVM algorithm is a learning retrieval function that employs pairwise ranking methods to adaptively sort results based on how 'relevant' they are for a specific query. The ranking SVM function uses a mapping function to describe the match between a search query and the features of each of the possible results.
The PAPRIKA method can be easily demonstrated via the simple example of determining the point values (weights) on the criteria for a value model with just three criteria – denoted by 'a', 'b' and 'c' – and two categories within each criterion – '1' and '2', where 2 is the higher ranked category. [1] This value model's six-point values ...
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.
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 .
To quantile normalize two or more distributions to each other, without a reference distribution, sort as before, then set to the average (usually, arithmetic mean) of the distributions. So the highest value in all cases becomes the mean of the highest values, the second highest value becomes the mean of the second highest values, and so on.
1 October 2010 () No Proprietary: CLI, GUI: ROOT: ROOT Analysis Framework 6.24.00 (15 April 2021) Yes GNU GPL: GUI: C++ C++, Python SageMath >100 developers worldwide 9.5 (30 January 2022; 2 years ago (10] Yes GNU GPL: CLI & GUI: Python, Cython Python Salstat: Alan J. Salmoni, Mark Livingstone 16 May 2014 () Yes GNU GPL
In apportionment theory, rank-index methods [1]: Sec.8 are a set of apportionment methods that generalize the divisor method. These have also been called Huntington methods , [ 2 ] since they generalize an idea by Edward Vermilye Huntington .
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.