9783030243586 - model selection and error estimation in a nutshell: 15 (modeling and optimization in science and technologies, 15) de oneto, luca (9 resultados)
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Editorial: Springer, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Hardcover. Condición: As New. 1. Auflage. from Germany, will be dispatched immediately.
Idioma: Inglés
Editorial: Springer, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Condición: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
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Editorial: Springer International Publishing, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - How can we select the best performing data-driven model How can we rigorously estimate its generalization error Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in other words…, by upper bounding the true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory has been considered only an abstract theoretical framework, useful for inspiring new learning approaches, but with limited applicability to practical problems. The purpose of this book is to give an intelligible overview of the problems of model selection and error estimation, by focusing on the ideas behind the different statistical learning theory approaches and simplifying most of the technical aspects with the purpose of making them more accessible and usable in practice. The book starts by presenting the seminal works of the 80's and includes the most recent results. It discusses open problems and outlines future directions for research.
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Editorial: Springer Nature Switzerland AG, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
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Editorial: Springer International Publishing Jul 2019, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -How can we select the best performing data-driven model How can we rigorously estimate its generalization error Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or…, in other words, by upper bounding the true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory has been considered only an abstract theoretical framework, useful for inspiring new learning approaches, but with limited applicability to practical problems. The purpose of this book is to give an intelligible overview of the problems of model selection and error estimation, by focusing on the ideas behind the different statistical learning theory approaches and simplifying most of the technical aspects with the purpose of making them more accessible and usable in practice. The book starts by presenting the seminal works of the 80's and includes the most recent results. It discusses open problems and outlines future directions for research. 148 pp. Englisch.
Idioma: Inglés
Editorial: Springer International Publishing, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Librería: moluna, Greven, Alemaniamoluna
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Reviews the main approaches to problems of model selection and error estimation Simplifies most of the technical aspects focusing on the applicability of the approachesPresents the intuitions behind the methods, the f…ormalism, and practical al.
Idioma: Inglés
Editorial: Springer, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Editorial: Springer, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Idioma: Inglés
Editorial: Springer, Springer Jul 2019, 2019
Serie: Libro 11 de 14 - Modeling and Optimization in Science and Technologies
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 106,99
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -How can we select the best performing data-driven model How can we rigorously estimate its generalization error Statistical learning theory answers these questions by deriving non-asymptotic bounds on the generalization error of a model or, in… other words, by upper bounding the true error of the learned model based just on quantities computed on the available data. However, for a long time, Statistical learning theory has been considered only an abstract theoretical framework, useful for inspiring new learning approaches, but with limited applicability to practical problems. The purpose of this book is to give an intelligible overview of the problems of model selection and error estimation, by focusing on the ideas behind the different statistical learning theory approaches and simplifying most of the technical aspects with the purpose of making them more accessible and usable in practice. The book starts by presenting the seminal works of the 80¿s and includes the most recent results. It discusses open problems and outlines future directions for research.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 148 pp. Englisch.
