9783319836751 - machine learning paradigms: artificial immune systems and their applications in software personalization: 118 di sotiropoulos, dionisios n.; tsihrintzis, george a. (11 risultati)
Lingua: Inglese
Editore: Springer, 2018
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Condizione: New. Softcover reprint of the original 1st ed. 2017 edition NO-PA16APR2015-KAP.
Lingua: Inglese
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Taschenbuch. Condizione: Neu. Machine Learning Paradigms | Artificial Immune Systems and their Applications in Software Personalization | Dionisios N. Sotiropoulos (u. a.) | Taschenbuch | Intelligent Systems Reference Library | xvi | Englisch | 2018 | Springer | EAN 9783319836751 | Verantwortliche Person für die EU: Springer Ver…lag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Lingua: Inglese
Editore: Springer International Publishing, Springer International Publishing, 2018
Serie: Intelligent Systems Reference Library, Libro 89 di 188. Libro 89 di 188 - Intelligent Systems Reference Library
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems.…Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process. The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems.The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.
Lingua: Inglese
Editore: Springer, 2018
Serie: Intelligent Systems Reference Library, Libro 89 di 188. Libro 89 di 188 - Intelligent Systems Reference Library
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Paperback. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Lingua: Inglese
Editore: Springer, 2018
Serie: Intelligent Systems Reference Library, Libro 89 di 188. Libro 89 di 188 - Intelligent Systems Reference Library
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Condizione: new. Questo è un articolo print on demand.
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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 -The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine le…arning systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process. The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems.The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her. 344 pp. Englisch.
Lingua: Inglese
Editore: Springer International Publishing, 2018
Serie: Intelligent Systems Reference Library, Libro 89 di 188. Libro 89 di 188 - Intelligent Systems Reference Library
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent machine-learning methodologies based on artificial immune systemsProvides experimental justification about the validity of artificial immune systems as an alternative machine learning paradigmIncludes… an extensive review of .
Lingua: Inglese
Editore: Springer, 2018
Serie: Intelligent Systems Reference Library, Libro 89 di 188. Libro 89 di 188 - Intelligent Systems Reference Library
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Condizione: New. Print on Demand.
Lingua: Inglese
Editore: Springer, 2018
Serie: Intelligent Systems Reference Library, Libro 89 di 188. Libro 89 di 188 - Intelligent Systems Reference Library
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Lingua: Inglese
Editore: Springer, Springer Jun 2018, 2018
Serie: Intelligent Systems Reference Library, Libro 89 di 188. Libro 89 di 188 - Intelligent Systems Reference Library
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learni…ng systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process. The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems.The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 344 pp. Englisch.
