Learning to Quantify / by Andrea Esuli, Alessandro Fabris, Alejandro Moreo, Fabrizio Sebastiani.
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 to classif...
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| Superior document: | The Information Retrieval Series, 47 |
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| VerfasserIn: | |
| Place / Publishing House: | Cham : : Springer International Publishing :, Imprint: Springer,, 2023. |
| Year of Publication: | 2023 |
| Edition: | 1st ed. 2023. |
| Language: | English |
| Series: | The Information Retrieval Series,
47 |
| Physical Description: | 1 online resource (XVI, 137 p. 1 illus.) |
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