Sampling techniques supervised unsupervised (20 risultati)

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  • Lingua: Inglese

    Editore: Springer, 2020

    3030293513 / 9783030293512

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: Springer, 2019

    3030293483 / 9783030293482

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  • Lingua: Inglese

    Editore: Springer, 2020

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    Condizione: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.

  • Lingua: Inglese

    Editore: Springer, 2019

    3030293483 / 9783030293482

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    Condizione: New. pp. XIII, 232 40 illus., 30 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP.

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    Lingua: Inglese

    Editore: Springer, 2020

    3030293513 / 9783030293512

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    Taschenbuch. Condizione: Neu. Sampling Techniques for Supervised or Unsupervised Tasks | Frédéric Ros (u. a.) | Taschenbuch | Unsupervised and Semi-Supervised Learning | xiii | Englisch | 2020 | Springer | EAN 9783030293512 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

  • Lingua: Inglese

    Editore: Springer, 2019

    3030293483 / 9783030293482

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    Hardcover. Condizione: Brand New. 248 pages. 9.25x6.10x0.75 inches. In Stock.

  • Lingua: Inglese

    Editore: Springer, 2020

    3030293513 / 9783030293512

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    Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli.

  • Lingua: Inglese

    Editore: Springer, Berlin, Springer, 2019

    3030293483 / 9783030293482

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    Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli.

  • Lingua: Inglese

    Editore: Springer, 2020

    3030293513 / 9783030293512

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    Softcover. Condizione: gut. 2020. Sampling Techniques for Supervised or Unsupervised Tasks In deutscher Sprache. pages.

  • Lingua: Inglese

    Editore: Springer, 2020

    3030293513 / 9783030293512

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  • Lingua: Inglese

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  • Lingua: Inglese

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    Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli 248 pp. Englisch.

  • Lingua: Inglese

    Editore: Berlin Springer International Publishing Springer Nov 2019, 2019

    3030293483 / 9783030293482

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    Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli 232 pp. Englisch.

  • Lingua: Inglese

    Editore: Springer International Publishing, 2020

    3030293513 / 9783030293512

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a comprehensive description of sampling techniques for unsupervised and supervised tasksDescribe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionalityAddresses t.

  • Lingua: Inglese

    Editore: Springer International Publishing, 2019

    3030293483 / 9783030293482

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a comprehensive description of sampling techniques for unsupervised and supervised tasksDescribe implementation and evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionalityAddresses t.

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    Editore: Springer, 2020

    3030293513 / 9783030293512

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  • Lingua: Inglese

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    Condizione: New. Print on Demand pp. XIII, 232 40 illus., 30 illus. in color.

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    Condizione: New. PRINT ON DEMAND pp. XIII, 232 40 illus., 30 illus. in color.

  • Lingua: Inglese

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    Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the ¿eld and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data.'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central ArkansasSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 248 pp. Englisch.