Isbn: 9783110518702 - dynamic fuzzy machine learning (20 risultati)

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  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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  • Lingua: Inglese

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  • Lingua: Inglese

    Editore: De Gruyter, 2017

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  • Lingua: Inglese

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  • Lingua: Inglese

    Editore: De Gruyter, 2017

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  • Lingua: Inglese

    Editore: De Gruyter, 2017

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    Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 338 | Sprache: Englisch | Produktart: Bücher | Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.…

  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections

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    Condizione: New. In English.

  • Lingua: Inglese

    Editore: De Gruyter, 2017

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    Da: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand

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  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH

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    Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.…

  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK

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  • Lingua: Inglese

    Editore: De Gruyter, DE, 2017

    3110518708 / 9783110518702

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    Hardback. Condizione: New. Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.…

  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: Majestic Books, Hounslow, Regno UnitoMajestic Books

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  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books

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    Hardcover. Condizione: Brand New. 440 pages. 9.45x6.69x1.02 inches. In Stock.

  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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  • Lingua: Inglese

    Editore: De Gruyter, DE, 2017

    3110518708 / 9783110518702

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    Da: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United

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    Hardback. Condizione: New. Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning.…

  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.

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    Condizione: New. 2017. Hardcover. . . . . .

  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, GermaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer

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    Condizione: gut. 2017. Dynamic Fuzzy Machine Learning In deutscher Sprache. pages.

  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Da: Kennys Bookstore, Olney, MD, U.S.A.Kennys Bookstore

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  • Lingua: Inglese

    Editore: De Gruyter, 2017

    3110518708 / 9783110518702

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    Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Fanzhang Li, Zhang Li, Zhang Zhao, Soochow University, Suzhou, China Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of.…

  • Lingua: Inglese

    Editore: De Gruyter, De Gruyter Dez 2017, 2017

    3110518708 / 9783110518702

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    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 -Machine learning is widely used for data analysis. Dynamic fuzzy data are one of the most difficult types of data to analyse in the field of big data, cloud computing, the Internet of Things, and quantum information. At present, the processing of this kind of data is not very mature. The authors carried out more than 20 years of research, and show in this book their most important results. The seven chapters of the book are devoted to key topics such as dynamic fuzzy machine learning models, dynamic fuzzy self-learning subspace algorithms, fuzzy decision tree learning, dynamic concepts based on dynamic fuzzy sets, semi-supervised multi-task learning based on dynamic fuzzy data, dynamic fuzzy hierarchy learning, examination of multi-agent learning model based on dynamic fuzzy logic. This book can be used as a reference book for senior college students and graduate students as well as college teachers and scientific and technical personnel involved in computer science, artificial intelligence, machine learning, automation, data analysis, mathematics, management, cognitive science, and finance. It can be also used as the basis for teaching the principles of dynamic fuzzy learning. 338 pp. Englisch.…