標(biāo)題: Titlebook: Learning to Quantify; Andrea Esuli,Alessandro Fabris,Fabrizio Sebastiani Book‘‘‘‘‘‘‘‘ 2023 The Editor(s) (if applicable) and The Author(s) [打印本頁] 作者: 尖酸好 時(shí)間: 2025-3-21 19:14
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書目名稱Learning to Quantify網(wǎng)絡(luò)公開度
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書目名稱Learning to Quantify被引頻次
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書目名稱Learning to Quantify讀者反饋
書目名稱Learning to Quantify讀者反饋學(xué)科排名
作者: LIMIT 時(shí)間: 2025-3-21 23:18
Learning to Quantify978-3-031-20467-8Series ISSN 1871-7500 Series E-ISSN 2730-6836 作者: Pulmonary-Veins 時(shí)間: 2025-3-22 03:36 作者: Genteel 時(shí)間: 2025-3-22 06:58 作者: critic 時(shí)間: 2025-3-22 11:59 作者: cardiac-arrest 時(shí)間: 2025-3-22 14:13
https://doi.org/10.1007/978-3-031-20467-8Information Retrieval; Machine Learning; Supervised Learning; Data Mining; Prevalence Estimation; Class P作者: 即席 時(shí)間: 2025-3-22 19:42
dictions in the EU’s approach to Central and Eastern European states in the period 2004–2014 and shows how the puzzles that motivated this book arose. Drawing on my practical experience working for the EU in Ukraine and on analysis of the wider political context it highlights connections between ide作者: 額外的事 時(shí)間: 2025-3-22 22:30
Andrea Esuli,Alessandro Fabris,Alejandro Moreo,Fabrizio Sebastianidistinction of the borderscape from the wider social world by also connecting it to political questions of identities and orders, drawing on and updating previous work in the ‘IBO tradition’. This chapter also identifies key socio-political, spatial and temporal underpinnings of my research and expl作者: 哄騙 時(shí)間: 2025-3-23 02:14
Andrea Esuli,Alessandro Fabris,Alejandro Moreo,Fabrizio Sebastianibelonging, and by drawing upon?social theories that approach the changing nature of the late modernity, and new ways of social participation. The results of our study?indicate that a shared sense of belonging to a community that encourages personal expression in the face of oppression may make socia作者: dysphagia 時(shí)間: 2025-3-23 07:25 作者: 占卜者 時(shí)間: 2025-3-23 11:19 作者: 人類 時(shí)間: 2025-3-23 15:12 作者: 救護(hù)車 時(shí)間: 2025-3-23 19:18
es–are integrally intertwined with identity construction and trajectories.Chapter authors examine issues of identity with participants ranging from first graders to pre-service and in-service teachers, to physics doctoral students, to show ways in which identity work is a vital (albeit still underem作者: 是他笨 時(shí)間: 2025-3-24 00:50 作者: 榨取 時(shí)間: 2025-3-24 02:54 作者: FADE 時(shí)間: 2025-3-24 09:27 作者: 富足女人 時(shí)間: 2025-3-24 13:15 作者: mitten 時(shí)間: 2025-3-24 15:37
1871-7500 o be used for evaluating the quality of the returned predict.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,作者: pantomime 時(shí)間: 2025-3-24 20:43 作者: 治愈 時(shí)間: 2025-3-25 01:32 作者: 徹底明白 時(shí)間: 2025-3-25 05:35
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.作者: 利用 時(shí)間: 2025-3-25 07:35 作者: AVANT 時(shí)間: 2025-3-25 12:55 作者: CRATE 時(shí)間: 2025-3-25 15:49
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.作者: 返老還童 時(shí)間: 2025-3-25 20:59 作者: Expertise 時(shí)間: 2025-3-26 02:27 作者: 前兆 時(shí)間: 2025-3-26 07:01 作者: 灌溉 時(shí)間: 2025-3-26 11:42 作者: 織布機(jī) 時(shí)間: 2025-3-26 12:40
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 作者: 拉開這車床 時(shí)間: 2025-3-26 19:13 作者: Gullible 時(shí)間: 2025-3-27 00:08 作者: Etymology 時(shí)間: 2025-3-27 05:04 作者: Chivalrous 時(shí)間: 2025-3-27 07:06
The Case for Quantification,ons and their estimation, dataset shift, and the various subtypes of dataset shift which are relevant to the quantification endeavour. In this chapter we also argue why using classification techniques for estimating class distributions is suboptimal, and we then discuss why learning to quantify has 作者: pineal-gland 時(shí)間: 2025-3-27 11:05 作者: 開花期女 時(shí)間: 2025-3-27 16:01 作者: 委托 時(shí)間: 2025-3-27 17:47
Methods for Learning to Quantify, proposed over the years. These methods belong to two main categories, depending on whether they have an aggregative nature (i.e., they require the classification of all individual unlabelled items as an intermediate step) or a non-aggregative nature (i.e., they perform no classification of individu作者: transient-pain 時(shí)間: 2025-3-28 00:24 作者: 使成整體 時(shí)間: 2025-3-28 05:31
The Quantification Landscape, of quantification research, from its beginnings to the most recent quantification-based “shared tasks”; the landscape of quantification-based, publicly available software libraries; visualization tools specifically oriented to displaying the results of quantification-based experiments; and other ta
