Quantification

Fabrizio Sebastiani

Director of Research

Alejandro Moreo

Senior Researcher

Andrea Esuli

Director of Research

In a number of applications involving classification, the final goal is not determining which class individual unlabelled instances belong to, but estimating the prevalence of each class in the unlabelled data. In recent years it has been pointed out that, in these cases, it would make sense to directly optimise machine learning algorithms for this goal rather than just optimising the classifier’s ability to label individual instances. The task of training estimators of class prevalence via supervised learning is known as learning to quantify, or, more simply, quantification.