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Data Clustering and Image Segmentation Through Genetic Algorithms: Emerging Research and Opportunities, S. Dash, B.K. Tripathy


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Автор: S. Dash, B.K. Tripathy
Название:  Data Clustering and Image Segmentation Through Genetic Algorithms: Emerging Research and Opportunities
ISBN: 9781522563198
Издательство: Mare Nostrum (Eurospan)
Классификация:



ISBN-10: 1522563199
Обложка/Формат: Hardback
Страницы: 160
Вес: 0.81 кг.
Дата издания: 30.09.2022
Серия: Computing & IT
Язык: English
Размер: 186 x 232 x 18
Читательская аудитория: Professional and scholarly
Ключевые слова: Data capture & analysis,Information technology: general issues, COMPUTERS / Databases / General,COMPUTERS / General,COMPUTERS / Image Processing
Подзаголовок: Emerging research and opportunities
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Поставляется из: Англии
Описание: As computers are being used more and more to solve complex problems, the application of biology or natural evolution principles to the study and design of human systems helps provide efficient optimization algorithms.

Data Clustering and Image Segmentation Through Genetic Algorithms: Emerging Research and Opportunities is an essential reference source that discusses applications of bio-inspired algorithms in data mining, computer vision, image processing, and pattern recognition, as well as methods of designing competent algorithms based on decomposition principles. Featuring research on topics such as cluster analysis, metaheuristic optimization, and image processing, this book is ideally designed for IT professionals, computer engineers, researchers, academicians, and upper-level students seeking coverage on how to develop efficient clustering algorithms.


Data Clustering: Theory, Algorithms, and Applications

Автор: Guojun Gan
Название: Data Clustering: Theory, Algorithms, and Applications
ISBN: 0898716233 ISBN-13(EAN): 9780898716238
Издательство: Mare Nostrum (Eurospan)
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Цена: 112860.00 T
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Описание: Cluster analysis is an unsupervised process that divides a set of objects into homogeneous groups. This book starts with basic information on cluster analysis, including the classification of data and the corresponding similarity measures, followed by the presentation of over 50 clustering algorithms in groups according to some specific baseline methodologies such as hierarchical, centre-based, and search-based methods. As a result, readers and users can easily identify an appropriate algorithm for their applications and compare novel ideas with existing results. The book also provides examples of clustering applications to illustrate the advantages and shortcomings of different clustering architectures and algorithms. Application areas include pattern recognition, artificial intelligence, information technology, image processing, biology, psychology, and marketing. Suitable as a textbook for an introductory course in cluster analysis or as source material for a graduate-level introduction to data mining.

Modern Technologies for Big Data Classification and Clustering

Автор: Seetha Hari, Murty M. Narasimha, Tripathy B. K.
Название: Modern Technologies for Big Data Classification and Clustering
ISBN: 1522528059 ISBN-13(EAN): 9781522528050
Издательство: Mare Nostrum (Eurospan)
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Цена: 208830.00 T
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Описание: Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage.Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.Topics Covered:The many academic areas covered in this publication include, but are not limited to:Data visualizationDistributed Computing SystemsOpinion MiningPrivacy and securityRisk analysisSocial Network AnalysisText Data AnalyticsWeb Data Analytics

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering

Автор: Isra?l C?sar Lerman
Название: Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
ISBN: 1447167910 ISBN-13(EAN): 9781447167914
Издательство: Springer
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Цена: 153720.00 T
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Описание: Preface.- On Some Facets of the Partition Set of a Finite Set.- Two Methods of Non-hierarchical Clustering.- Structure and Mathematical Representation of Data.- Ordinal and Metrical Analysis of the Resemblance Notion.- Comparing Attributes by a Probabilistic and Statistical Association I.- Comparing Attributes by a Probabilistic and Statistical Association II.- Comparing Objects or Categories Described by Attributes.- The Notion of "Natural" Class, Tools for its Interpretation. The Classifiability Concept.- Quality Measures in Clustering.- Building a Classification Tree.- Applying the LLA Method to Real Data.- Conclusion and Thoughts for Future Works



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