Model selection error estimation di oneto luca (23 risultati)
Lingua: Inglese
Editore: Springer, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Lingua: Inglese
Editore: Springer, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Lingua: Inglese
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Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Lingua: Inglese
Editore: Springer, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Condizione: New. pp. 132 1st ed. 2020 edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Lingua: Inglese
Editore: Springer Nature, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Paperback. Condizione: Brand New. 148 pages. 9.25x6.10x0.34 inches. In Stock.
Altre immaginiLingua: Inglese
Editore: Springer, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Model Selection and Error Estimation in a Nutshell | Luca Oneto | Taschenbuch | Modeling and Optimization in Science and Technologies | xiii | Englisch | 2020 | Springer | EAN 9783030243616 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]ha…rtmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer International Publishing, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: 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 oth…er 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.
Lingua: Inglese
Editore: Springer International Publishing, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
- Rilegato
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: 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 word…s, 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.
Lingua: Inglese
Editore: Springer Nature Switzerland AG, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
- Brossura
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Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condizione: new. Questo è un articolo print on demand.
Lingua: Inglese
Editore: Springer International Publishing Aug 2020, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: 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.
Lingua: Inglese
Editore: Springer International Publishing Jul 2019, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
- Rilegato
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
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Buch. Condizione: 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 o…r, 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.
Lingua: Inglese
Editore: Springer International Publishing, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
- Brossura
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Da: moluna, Greven, Germaniamoluna
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Condizione: 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…formalism, and practical al.
Lingua: Inglese
Editore: Springer International Publishing, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
- Rilegato
- Print on Demand
Da: moluna, Greven, Germaniamoluna
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Condizione: 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…formalism, and practical al.
Lingua: Inglese
Editore: Springer, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand pp. 132.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND pp. 132.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. PRINT ON DEMAND.
Lingua: Inglese
Editore: Springer, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: preigu, Osnabrück, Germaniapreigu
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Buch. Condizione: Neu. Model Selection and Error Estimation in a Nutshell | Luca Oneto | Buch | Modeling and Optimization in Science and Technologies | xiii | Englisch | 2019 | Springer | EAN 9783030243586 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]spri…nger[dot]com | Anbieter: preigu Print on Demand.
Lingua: Inglese
Editore: Springer, Springer Aug 2020, 2020
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
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Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
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EUR 106,99
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Taschenbuch. Condizione: 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 mode…l 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.
Lingua: Inglese
Editore: Springer, Springer Jul 2019, 2019
Serie: Libro 11 di 14 - Modeling and Optimization in Science and Technologies
- Rilegato
- Print on Demand
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germaniabuchversandmimpf2000
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 106,99
EUR 60,00 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: 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, i…n 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.
