The Case for Quantification
Andrea Esuli, Alessandro Fabris, Alejandro Moreo, Fabrizio Sebastiani · The information retrieval series · 2023
Abstract This chapter sets the stage for the rest of the book by introducing notions fundamental to quantification, such as class proportions, class distributions and their estimation, dataset shift, and the various subtypes of dataset shift which are relevant to the quantification endeavour. In this chapter we also argue why using classification techniques for estimating class distributions is suboptimal, and we then discuss why learning to quantify has evolved as a task of its own, rather than remaining a by-product of classification.