Sensitivity index to measure dependence on parameters for rankings and top- k rankings - Université Lumière Lyon 2
Article Dans Une Revue Journal of Applied Statistics Année : 2020

Sensitivity index to measure dependence on parameters for rankings and top- k rankings

Résumé

In a multivariate framework, ranking a data set can be done by using an aggregation function in order to obtain a global score for each individual, and then by using these scores to rank the individuals. The choice of the aggregation function (e.g. a weighted sum) and the choice of the parameters of the function (e.g. the weights) may have a great influence on the obtained ranking. We introduce in this communication a ratio index that can quantify the sensitivity of the data set ranking up to a change of weights. This index is investigated in the general case and in the restricted case of top k rankings. We also illustrate the interest to use such an index to analyze ranked data sets.
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Dates et versions

hal-02610998 , version 1 (18-05-2020)

Identifiants

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Antoine Rolland, Jairo Cugliari. Sensitivity index to measure dependence on parameters for rankings and top- k rankings. Journal of Applied Statistics, 2020, 47 (7), pp.1191-1207. ⟨10.1080/02664763.2019.1671963⟩. ⟨hal-02610998⟩
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