Learning to Quantify by Andrea Esuli (English) Paperback Book

Description: Learning to Quantify by Andrea Esuli, Alessandro Fabris, Alejandro Moreo, Fabrizio Sebastiani Estimated delivery 3-12 business days Format Paperback Condition Brand New Description 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. Author Biography Andrea Esuli is a tenured Senior Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-modal classification, technology-assisted review, and representation learning.Alessandro Fabris is a PhD student at the University of Padova. His research interests include learning to quantify, and the fairness and bias of retrieval and classification systems.Alejandro Moreo is a tenured Researcher at the Italian National Council of Research. His research interests include learning to quantify, deep learning for text analysis, cross-lingual text classification, authorship analysis, and representation learning.Fabrizio Sebastiani is a tenured Director of Research at the Italian National Council of Research. His research interests include learning to quantify, cross-lingual text classification, technology-assisted review, authorship analysis, and representation learning. Details ISBN 3031204662 ISBN-13 9783031204661 Title Learning to Quantify Author Andrea Esuli, Alessandro Fabris, Alejandro Moreo, Fabrizio Sebastiani Format Paperback Year 2023 Pages 137 Edition 1st Publisher Springer International Publishing AG GE_Item_ID:144079581; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

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End Time: 2024-11-27T10:06:23.000Z

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