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Machine Learning Paradigms, Dionisios N. Sotiropoulos; George A. Tsihrintzis


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Автор: Dionisios N. Sotiropoulos; George A. Tsihrintzis
Название:  Machine Learning Paradigms
ISBN: 9783319471921
Издательство: Springer
Классификация:

ISBN-10: 3319471929
Обложка/Формат: Hardback
Страницы: 327
Вес: 0.68 кг.
Дата издания: 2017
Серия: Intelligent systems reference library
Язык: English
Издание: 2017 ed.
Иллюстрации: 53 black & white illustrations, 18 colour illustrations, biography
Размер: 234 x 156 x 21
Читательская аудитория: Professional & vocational
Подзаголовок: Artificial immune systems and their applications in software personalization
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.
Дополнительное описание: Introduction.- Machine Learning.- The Class Imbalance Problem.- Addressing the Class Imbalance Problem.- Machine Learning Paradigms.- Immune System Fundamentals.- Artificial Immune Systems.- Experimental Evaluation of Artificial Immune System-based Learni



Paradigms of Artificial Intelligence Programming,

Автор: Peter Norvig
Название: Paradigms of Artificial Intelligence Programming,
ISBN: 1558601910 ISBN-13(EAN): 9781558601918
Издательство: Elsevier Science
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Цена: 9599.00 р.
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Описание: Paradigms of AI Programming teaches advanced Common Lisp techniques in the context of building major AI systems.

Machine Learning

Автор: Kevin Murphy
Название: Machine Learning
ISBN: 0262018020 ISBN-13(EAN): 9780262018029
Издательство: MIT Press
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Цена: 18622.00 р.
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Описание:

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Data Mining: Foundations and Intelligent Paradigms

Автор: Dawn E. Holmes; Lakhmi C. Jain
Название: Data Mining: Foundations and Intelligent Paradigms
ISBN: 3642435467 ISBN-13(EAN): 9783642435461
Издательство: Springer
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Цена: 29209.00 р.
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Описание: This volume, which includes the latest research on data mining and its applications to financial modeling, presents its material in an easy-to-consult handbook style and is aimed at a broad audience that includes both specialists and non-specialists alike.

Advanced Computational Intelligence Paradigms in Healthcare 6

Автор: Sheryl Brahnam; Lakhmi C. Jain
Название: Advanced Computational Intelligence Paradigms in Healthcare 6
ISBN: 3642446248 ISBN-13(EAN): 9783642446245
Издательство: Springer
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Цена: 20896.00 р.
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Описание: Covering a plethora of aspects of this developing field, this book explores the latest applications of virtual reality to psychotherapy, rehabilitation and neurological assessment. It ranges from VR`s use in conditions from PTSD to amblyopia in children.

Innovations in Neural Information Paradigms and Applications

Автор: Monica Bianchini; Marco Maggini; Franco Scarselli
Название: Innovations in Neural Information Paradigms and Applications
ISBN: 3642040020 ISBN-13(EAN): 9783642040023
Издательство: Springer
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Цена: 23058.00 р.
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Описание: Presenting the fundamentals and practical applications of neural information systems, this volume presents the recent developments in the field. Self-organizing structures, neural grammar networks and model complexity are among the many topics discussed.

Data Mining: Foundations and Intelligent Paradigms

Автор: Dawn E. Holmes; Lakhmi C. Jain
Название: Data Mining: Foundations and Intelligent Paradigms
ISBN: 3642430937 ISBN-13(EAN): 9783642430930
Издательство: Springer
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Цена: 23508.00 р.
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Описание: However, in compiling a volume titled "DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification" we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Data Mining: Foundations and Intelligent Paradigms

Автор: Dawn E. Holmes; Lakhmi C. Jain
Название: Data Mining: Foundations and Intelligent Paradigms
ISBN: 3642434290 ISBN-13(EAN): 9783642434297
Издательство: Springer
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Цена: 18284.00 р.
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Описание: Data mining is a rapidly growing research area in computer science and statistics. Volume 2 of this three-volume series covers theoretical aspects of the subject, including statistical, Bayesian, time-series and others relevant to health informatics.

Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Автор: Kelleher John D., Macnamee Brian, D`Arcy Aoife
Название: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
ISBN: 0262029448 ISBN-13(EAN): 9780262029445
Издательство: MIT Press
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Цена: 13543.00 р.
Наличие на складе: Нет в наличии.

Описание:

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.

After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.

Advanced Computational Intelligence Paradigms in Healthcare - 3

Автор: Margarita Sordo; Sachin Vaidya
Название: Advanced Computational Intelligence Paradigms in Healthcare - 3
ISBN: 3642096441 ISBN-13(EAN): 9783642096440
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This volume details the latest state-of-the-art research on computational intelligence paradigms in healthcare in the intelligent agent environment. The book presents seven chapters selected from the rapidly growing application areas of computational intelligence to healthcare systems.


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