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

Abstract : 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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Soumis le : lundi 18 mai 2020 - 07:59:24
Dernière modification le : jeudi 28 mai 2020 - 03:30:59

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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, Taylor & Francis (Routledge), 2020, 47 (7), pp.1191-1207. ⟨10.1080/02664763.2019.1671963⟩. ⟨hal-02610998⟩

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