%0 Journal Article
%T Sensitivity index to measure dependence on parameters for rankings and top- k rankings
%+ Entrepôts, Représentation et Ingénierie des Connaissances (ERIC)
%A Rolland, Antoine
%A Cugliari, Jairo
%< avec comité de lecture
%@ 0266-4763
%J Journal of Applied Statistics
%I Taylor & Francis (Routledge)
%V 47
%N 7
%P 1191-1207
%8 2020-05-18
%D 2020
%R 10.1080/02664763.2019.1671963
%K top-k list
%K sensitivity
%K index
%K Ranking
%K top-k list
%Z Computer Science [cs]/Operations Research [math.OC]
%Z Mathematics [math]/Statistics [math.ST]Journal articles
%X 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.
%G English
%2 https://hal.univ-lyon2.fr/hal-02610998/document
%2 https://hal.univ-lyon2.fr/hal-02610998/file/ROLLAND_CUGLIARI_JAS.pdf
%L hal-02610998
%U https://hal.univ-lyon2.fr/hal-02610998
%~ UNIV-LYON1
%~ UNIV-LYON2
%~ ERIC
%~ TDS-MACS
%~ LYON2
%~ UDL
%~ UNIV-LYON