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Learning to Quantify

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This open access book provides an introduction and an overview of learning to quantify (a.k.a. "quantification"), i.e. the task of training estimators of class proportions in unlabeled data by means of supervised learning. In data science, learning to quantify is a task of its own related...

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Bibliographic Details
Main Authors: Esuli, Andrea (Author), Fabris, Alessandro (Author), Moreo, Alejandro (Author), Sebastiani, Fabrizio (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2023.
Edition:1st ed. 2023.
Series:The Information Retrieval Series, 47
Subjects:
Information storage and retrieval systems.
Data mining.
Machine learning.
Information Storage and Retrieval.
Data Mining and Knowledge Discovery.
Machine Learning.
Online Access:Link to Metadata
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Learning to Quantify by Esuli, Andrea

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Learning to Quantify by Esuli, Andrea

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