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Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367381915 ISBN 13: 9780367381912
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Published by Routledge 2019-09-19, 2019
ISBN 10: 0367381915 ISBN 13: 9780367381912
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Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367381915 ISBN 13: 9780367381912
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Condition: Hervorragend. Zustand: Hervorragend | Seiten: 331 | Sprache: Englisch | Produktart: Bücher | This volume is one of the first books to provide an overview of the current research efforts and problems in this area. It discusses real-world applications that incorporate the cost of learning into the modeling process. The first part of the book describes well-established machine learning approaches for reducing data acquisition costs during training as well as approaches for reducing costs when systems must make predictions for new samples. The second part covers real-world applications, such as computer-aided medical diagnosis, that effectively trade off different types of costs.
Language: English
Published by Taylor & Francis Ltd, 2019
ISBN 10: 0367381915 ISBN 13: 9780367381912
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Balaji Krishnapuram is a senior R&D manager at Siemens Medical Solutions. He earned a Ph.D. in electrical and computer engineering from Duke University. His research interests include statistical data mining and information retrieval.
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This volume is one of the first books to provide an overview of the current research efforts and problems in this area. It discusses real-world applications that incorporate the cost of learning into the modeling process. The first part of the book describes well-established machine learning approaches for reducing data acquisition costs during training as well as approaches for reducing costs when systems must make predictions for new samples. The second part covers real-world applications, such as computer-aided medical diagnosis, that effectively trade off different types of costs.