Titlebook: Learning to Quantify; Andrea Esuli,Alessandro Fabris,Fabrizio Sebastiani Book‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applicable) and The Author(s)

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The Case for Quantification, 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.

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Advanced Topics,ntification for networked data, and quantification for streaming data. The chapter ends with a discussion on how to derive confidence intervals for the class prevalence estimates returned by quantification systems.

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Andrea Esuli,Alessandro Fabris,Alejandro Moreo,Fabrizio Sebastianile that are not part of their local community. In some cases, young people feel that belonging to online communities may serve as a refuge, a safe and stable place, in a modern society where everything else is moving. In this chapter we analyze how a sense of belonging develops for young members of

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