Sotiropoulos Dionisios (49 results)
Language: English
Published by Springer 2016
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Language: English
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Series: Intelligent Systems Reference Library, Book 89 of 188. Book 89 of 188 - Intelligent Systems Reference Library
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Condition: New. Softcover reprint of the original 1st ed. 2017 edition NO-PA16APR2015-KAP.
Language: English
Published by Springer 2016
Series: Intelligent Systems Reference Library, Book 89 of 188. Book 89 of 188 - Intelligent Systems Reference Library
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Language: English
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Series: Intelligent Systems Reference Library, Book 89 of 188. Book 89 of 188 - Intelligent Systems Reference Library
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Taschenbuch. Condition: 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 Verl…ag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Language: English
Published by Springer 2016
Series: Intelligent Systems Reference Library, Book 89 of 188. Book 89 of 188 - Intelligent Systems Reference Library
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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 344 | Sprache: Englisch | Produktart: Bücher | 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 learn…ing 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.
Language: English
Published by Springer 2018
Series: Intelligent Systems Reference Library, Book 89 of 188. Book 89 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer 2018
Series: Intelligent Systems Reference Library, Book 120 of 188. Book 120 of 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Language: English
Published by Springer 2018
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Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Language: English
Published by Springer 2018
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Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Language: English
Published by Springer 2018
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Machine Learning Paradigms : Advances in Data Analytics
Tsihrintzis, George A. (EDT); Sotiropoulos, Dionisios N. (EDT); Jain, Lakhmi C. (EDT)
Language: English
Published by Springer 2018
Series: Intelligent Systems Reference Library, Book 120 of 188. Book 120 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer 2018
Series: Intelligent Systems Reference Library, Book 120 of 188. Book 120 of 188 - Intelligent Systems Reference Library
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Taschenbuch. Condition: Neu. Machine Learning Paradigms | Advances in Data Analytics | George A. Tsihrintzis (u. a.) | Taschenbuch | xvi | Englisch | 2018 | Springer | EAN 9783030067779 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbie…ter: preigu.
Language: English
Published by Springer 2018
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Condition: New. Softcover reprint of the original 1st ed. 2019 edition NO-PA16APR2015-KAP.
Language: English
Published by Springer 2018
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Language: English
Published by Springer 2018
Series: Intelligent Systems Reference Library, Book 120 of 188. Book 120 of 188 - Intelligent Systems Reference Library
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Language: English
Published by Springer International Publishing, Springer International Publishing 2018
Series: Intelligent Systems Reference Library, Book 120 of 188. Book 120 of 188 - Intelligent Systems Reference Library
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores some of the emerging scientific and technological areas in which the need for data analytics arises and is likely to play a significant role in the years to come. At the dawn of the 4th Industrial Revolution, data analytics is em…erging as a force that drives towards dramatic changes in our daily lives, the workplace and human relationships. Synergies between physical, digital, biological and energy sciences and technologies, brought together by non-traditional data collection and analysis, drive the digital economy at all levels and offer new, previously-unavailable opportunities.The need for data analytics arises in most modern scientific disciplines, including engineering; natural-, computer- and information sciences; economics; business; commerce; environment; healthcare; and life sciences.Coming as the third volume under the general title MACHINE LEARNING PARADIGMS, the book includes an editorial note (Chapter 1) and an additional 12 chapters, and is divided into five parts: (1) Data Analytics in the Medical, Biological and Signal Sciences, (2) Data Analytics in Social Studies and Social Interactions, (3) Data Analytics in Traffic, Computer and Power Networks, (4) Data Analytics for Digital Forensics, and (5) Theoretical Advances and Tools for Data Analytics.This research book is intended for both experts/researchers in the field of data analytics, and readers working in the fields of artificial and computational intelligence as well as computer science in general who wish to learn more about the field of data analytics and its applications. An extensive list of bibliographic references at the end of each chapter guides readers to probe further into the application areas of interest to them.
Language: English
Published by Springer 2018
Series: Intelligent Systems Reference Library, Book 120 of 188. Book 120 of 188 - Intelligent Systems Reference Library
- Hardcover
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Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores some of the emerging scientific and technological areas in which the need for data analytics arises and is likely to play a significant role in the years to come. At the dawn of the 4th Industrial Revolution, data analytics is emerging…as a force that drives towards dramatic changes in our daily lives, the workplace and human relationships. Synergies between physical, digital, biological and energy sciences and technologies, brought together by non-traditional data collection and analysis, drive the digital economy at all levels and offer new, previously-unavailable opportunities.The need for data analytics arises in most modern scientific disciplines, including engineering; natural-, computer- and information sciences; economics; business; commerce; environment; healthcare; and life sciences.Coming as the third volume under the general title MACHINE LEARNING PARADIGMS, the book includes an editorial note (Chapter 1) and an additional 12 chapters, and is divided into five parts: (1) Data Analytics in the Medical, Biological and Signal Sciences, (2) Data Analytics in Social Studies and Social Interactions, (3) Data Analytics in Traffic, Computer and Power Networks, (4) Data Analytics for Digital Forensics, and (5) Theoretical Advances and Tools for Data Analytics.This research book is intended for both experts/researchers in the field of data analytics, and readers working in the fields of artificial and computational intelligence as well as computer science in general who wish to learn more about the field of data analytics and its applications. An extensive list of bibliographic references at the end of each chapter guides readers to probe further into the application areas of interest to them.
Language: English
Published by Springer 2018
Series: Intelligent Systems Reference Library, Book 120 of 188. Book 120 of 188 - Intelligent Systems Reference Library
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Machine Learning Paradigms: Advances in Data Analytics (Intelligent Systems Reference Library (149))
Language: English
Published by Springer 2018
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Language: English
Published by Springer 2018
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Language: English
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Published by Springer International Publishing 2016
Series: Intelligent Systems Reference Library, Book 89 of 188. Book 89 of 188 - Intelligent Systems Reference Library
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Condition: 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 .
