Learning Quantify by Esuli Andrea (16 results)
Learning to Quantify (The Information Retrieval Series)
Esuli, Andrea; Fabris, Alessandro; Moreo, Alejandro; Sebastiani, Fabrizio
Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
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Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
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Language: English
Published by Springer-Nature New York Inc, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
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Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
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Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 classification yet different from it, since estimating class proportions by simply classifying all data and counting the labels assigned by the classifier is known to often return inaccurate ('biased') class proportion estimates.The book introduces learning to quantify by looking at the supervised learning methods that can be used to perform it, at the evaluation measures and evaluation protocols that should be used for evaluating the quality of the returned predictions, at the numerous fields of human activity in which the use of quantification techniques may provide improved results with respect to the naive use of classification techniques, and at advanced topics in quantification research.The book is suitable to researchers, data scientists, or PhD students, who want to come up to speed with the state of the art in learning to quantify, but also to researchers wishing to apply data science technologies to fields of human activity (e.g., the social sciences, political science, epidemiology, market research) which focus on aggregate ('macro') data rather than on individual ('micro') data.
More imagesLanguage: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: Neu. Learning to Quantify | Andrea Esuli (u. a.) | Taschenbuch | The Information Retrieval Series | xvi | Englisch | 2023 | Springer | EAN 9783031204661 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: prei…gu.
Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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 classification yet different from it, since estimating class proportions by simply classifying all data and counting the labels assigned by the classifier is known to often return inaccurate (¿biased¿) class proportion estimates. The book introduces learning to quantify by looking at the supervised learning methods that can be used to perform it, at the evaluation measures and evaluation protocols that should be used for evaluating the quality of the returned predictions, at the numerous fields of human activity in which the use of quantification techniques may provide improved results with respect to the naive use of classification techniques, and at advanced topics in quantification research. The book is suitable to researchers, data scientists, or PhD students, who want to come up to speed with the state of the art in learning to quantify, but also to researchers wishing to apply data science technologies to fields of human activity (e.g., the social sciences, political science, epidemiology, market research) which focus on aggregate (¿macrö) data rather than on individual (¿micrö) data.
Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
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Condition: new. Questo è un articolo print on demand.
Language: English
Published by Springer Nature B.V., 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
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PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Language: English
Published by Springer Nature B.V., 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
- Print on Demand
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Language: English
Published by Springer International Publishing Mrz 2023, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 s…cience, learning to quantify is a task of its own related to classification yet different from it, since estimating class proportions by simply classifying all data and counting the labels assigned by the classifier is known to often return inaccurate ('biased') class proportion estimates.The book introduces learning to quantify by looking at the supervised learning methods that can be used to perform it, at the evaluation measures and evaluation protocols that should be used for evaluating the quality of the returned predictions, at the numerous fields of human activity in which the use of quantification techniques may provide improved results with respect to the naive use of classification techniques, and at advanced topics in quantification research.The book is suitable to researchers, data scientists, or PhD students, who want to come up to speed with the state of the art in learning to quantify, but also to researchers wishing to apply data science technologies to fields of human activity (e.g., the social sciences, political science, epidemiology, market research) which focus on aggregate ('macro') data rather than on individual ('micro') data. 156 pp. Englisch.
Learning to Quantify: 47 (The Information Retrieval Series)
Esuli, Andrea; Fabris, Alessandro; Moreo, Alejandro; Sebastiani, Fabrizio
Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, United KingdomMajestic Books
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Learning to Quantify: 47 (The Information Retrieval Series)
Esuli, Andrea; Fabris, Alessandro; Moreo, Alejandro; Sebastiani, Fabrizio
Language: English
Published by Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
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Language: English
Published by Springer, Berlin|Springer International Publishing|Istituto di Scienza e Tecnologie dell'Informazione|Springer, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
- Print on Demand
Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 learn…ing. In data science, learning to qu.
Language: English
Published by Springer, Palgrave Macmillan Mär 2023, 2023
Series: The Information Retrieval, Book 40 of 42. Book 40 of 42 - The Information Retrieval
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 scien…ce, learning to quantify is a task of its own related to classification yet different from it, since estimating class proportions by simply classifying all data and counting the labels assigned by the classifier is known to often return inaccurate (¿biased¿) class proportion estimates.The book introduces learning to quantify by looking at the supervised learning methods that can be used to perform it, at the evaluation measures and evaluation protocols that should be used for evaluating the quality of the returned predictions, at the numerous fields of human activity in which the use of quantification techniques may provide improved results with respect to the naive use of classification techniques, and at advanced topics in quantification research.The book is suitable to researchers, data scientists, or PhD students, who want to come up to speed with the state of the art in learning to quantify, but also to researchers wishing to apply data science technologies to fields of human activity (e.g., the social sciences, political science, epidemiology, market research) which focus on aggregate (¿macrö) data rather than on individual (¿micrö) data.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 156 pp. Englisch.
