Evaluation measures for quantification: an axiomatic approach

30/06/2020
Visto: 4 veces

Plenary talk at the Doctoral Consortium 2020

Quantification is the task of estimating, given a set of unlabelled items and a set of classes, the prevalence (or “relative frequency”) of each class. While the scientific community has devoted a lot of attention to devising more accurate quantification methods, it has not devoted much to discussing what properties an evaluation measure for quantification (EMQ) should enjoy, and which EMQs should be adopted as a result. This paper lays down a number of interesting properties that an EMQ may or may not enjoy, discusses if (and when) each of these properties is desirable, surveys the EMQs that have been used so far, and discusses whether they enjoy or not the above properties. As a result of this investigation, some of the EMQs that have been used in the literature turn out to be severely unfit, while others emerge as closer to what the quantification community actually needs. However, a significant result is that no existing EMQ satisfies all the properties identified as desirable, thus indicating that more research is needed in order to identify (or synthesize) a truly adequate EMQ.

Fabrizio Sebastiani Research staff at the Networked Multimedia Information Systems Laboratory (NeMIS), Istituto di Scienza e Tecnologie dell’Informazione “A. Faedo”


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Plenary talk at the Doctoral Consortium 2020
29 jun. 2020
Evaluation measures for quantification: an axiomatic approach
Plenary talk at the Doctoral Consortium 2020
30 jun. 2020