Clustering High--Dimensional Data, Francesco Masulli; Alfredo Petrosino; Stefano Rove

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.

Автор: Swagatam Das; Ajith Abraham; Amit Konar
Название: Metaheuristic Clustering
ISBN: 3642100716 ISBN-13(EAN): 9783642100710
Издательство: Springer
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Цена: 139750.00 T
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Описание: Cluster analysis means the organization of an unlabeled collection of objects into separate groups based on their similarity. With the use of several real world examples, this book formulates clustering as an optimization problem.

Автор: Viattchenin Dmitri A
Название: Heuristic Approach to Possibilistic Clustering: Algorithms a
ISBN: 3642355358 ISBN-13(EAN): 9783642355356
Издательство: Springer
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Цена: 130610.00 T
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Описание: In a new approach to possibilistic clustering, the sought clustering structure of the set is based directly on the formal definition of fuzzy cluster and possibilistic memberships are determined directly from the values of the pairwise similarity of objects.

Автор: Felipe M. G. Fran?a; Alberto Ferreira de Souza
Название: Intelligent Text Categorization and Clustering
ISBN: 3540856439 ISBN-13(EAN): 9783540856436
Издательство: Springer
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Цена: 139750.00 T
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Описание: Researchers have employed many intelligent techniques for text categorization and clustering, ranging from support vector machines and neural networks to Bayesian inference and algebraic methods, such as Latent Semantic Indexing. This volume offers a wide spectrum of research work developed for intelligent text categorization 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

Автор: Thomas Villmann; M. Biehl; Barbara Hammer; Michel
Название: Similarity-Based Clustering
ISBN: 3642018041 ISBN-13(EAN): 9783642018046
Издательство: Springer
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Цена: 95770.00 T
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Описание: Recent Developments and Biomedical Applications. .

Автор: Saman K. Halgamuge; Lipo Wang
Название: Classification and Clustering for Knowledge Discovery
ISBN: 3642065422 ISBN-13(EAN): 9783642065422
Издательство: Springer
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Цена: 194730.00 T
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Описание: This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees.

Автор: Felipe M. G. Fran?a; Alberto Ferreira de Souza
Название: Intelligent Text Categorization and Clustering
ISBN: 3642099297 ISBN-13(EAN): 9783642099298
Издательство: Springer
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Цена: 139750.00 T
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Описание: Spam filtering and web search are well-known applications of text categorization and clustering, but there are also many lesser known everyday uses. This text covers a wide spectrum of recent research developed for the field.