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Equivalently, each candidate feature corresponds to a ranking vector containing its rankings in these C ranked lists.
Section 2 reviews ordering methods: finding a ranking vector by optimization of a sum of Kendall's Tau rank-correlation coefficients and obtaining a ranking vector by dimension-reduction methods.
Each ranking vector is sorted in an ascending order.
The ranking vector of each candidate feature is sorted in an ascending order.
If one regards each element of the ranking vector as a digit, each ranking vector could represent a C digit number.
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MIC was ranked the first and PCF was ranked the fifth in the comparisons of the total Euclidean distance between the importance (DC, SPC) ranking vectors and the voting entropy.
The Kendall tau correlation between the ranked vectors of nationalities equals 0.69 ((p < 0.01)), showing a strong and significant correlation between the two rankings.
In general, Model (1) is run n times and introduces a rank vector in each run.
If for each j ( n ≥ j ≥ 1 ), there is i ∈ I such that u i = j, ( u 1, u 2, …, u n ) is called a complete rank vector, otherwise a noncomplete rank vector of players.
Hence, the rank vector of alternatives is from 1 to n defining a linear order for the alternatives.
And the cluster profile or mean ranks vector is defined by: p l = r ̄ j ∈ C l (5).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com