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Innovations in Fuzzy Clustering, Mika Sato-Ilic


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Автор: Mika Sato-Ilic
Название:  Innovations in Fuzzy Clustering
ISBN: 9783642070723
Издательство: Springer
Классификация: ISBN-10: 3642070728
Обложка/Формат: Paperback
Страницы: 165
Вес: 0.25 кг.
Дата издания: 2006
Серия: Studies in Fuzziness and Soft Computing
Язык: English
Размер: 234 x 156 x 9
Читательская аудитория: Science
Ссылка на Издательство: Link
Поставляется из: Германии
Описание: Clustering has been around for many decades and located itself in a uniquepositionasafundamentalconceptualandalgorithmiclandmark of data analysis. Almost since the very inception of fuzzy sets, the role and potential of these information granules in revealing and describing structureindatawasfullyacknowledgedandappreciated.Asamatter of fact, with the rapid growth of volumes of digital information, the role of clustering becomes even more visible and critical. Furthermore given the anticipated human centricity of the majority of artifacts of digitaleraandacontinuousbuildupofmountainsofdata, onebecomes fully cognizant of the growing role and an enormous potential of fuzzy sets and granular computing in the design of intelligent systems. In therecentyearsclusteringhasundergoneasubstantialmetamorphosis. Frombeinganexclusivelydata drivenpursuit, ithastransformeditself into a vehicle whose data centricity has been substantially augmented by the incorporation of domain knowledge thus giving rise to the next generation of knowledge-oriented and collaborative clustering. Interestingly enough, fuzzy clustering exhibits a dominant role in many developments of the technology of fuzzy sets including fuzzy modeling, fuzzy control, data mining, pattern recognition, and image processing. When browsing through numerous papers on fuzzy m- eling we can witness an important trend of a substantial reliance on fuzzy clustering being regarded as the general development tool. The same central position of fuzzy clustering becomes visible in pattern classi?ers and neurofuzzy systems. All in all, it becomes evident that further progress in fuzzy clustering is of vital relevance and benet to the overall progress of the area of fuzzy sets and their application


Financial models with levy processes and volatility clustering

Автор: Rachev, Svetlozar T. Kim, Young Shim Bianchi, Mich
Название: Financial models with levy processes and volatility clustering
ISBN: 0470482354 ISBN-13(EAN): 9780470482353
Издательство: Wiley
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Цена: 13464.00 р.
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Описание: * In this book, authors Rachev, Kim, Bianchi, and Fabozzi present readers with the notions of risk and their corresponding performance measures.

Genome Clustering

Автор: Alexander Bolshoy; Zeev Volkovich; Valery Kirzhner
Название: Genome Clustering
ISBN: 3642263402 ISBN-13(EAN): 9783642263408
Издательство: Springer
Цена: 20962.00 р.
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Описание: Knighting in sequence biology Edward N. Trifonov Genome classification, construction of phylogenetic trees, became today a major approach in studying evolutionary relatedness of various species in their vast - versity. Although the modern genome clustering delivers the trees which are very similar to those generated by classical means, and basic terminology is the same, the phenotypic traits and habitats are not anymore the playground for the classi- cation. The sequence space is the playground now. The phenotypic traits are - placed by sequence characteristics, "words", in particular. Matter-of-factually, the phenotype and genotype merged, to confusion of both classical and modern p- logeneticists. Accordingly, a completely new vocabulary of stringology, information theory and applied mathematics took over. And a new brand of scientists emerged - those who do know the math and, simultaneously, (do?) know biology. The book is written by the authors of this new brand. There is no way to test their literacy in biology, as no biologist by training would even try to enter into the elite circle of those who masters their almost occult language. But the army of - formaticians, formal linguists, mathematicians humbly (or aggressively) longing to join modern biology, got an excellent introduction to the field of genome cl- tering, written by the team of their kin.

Fuzzy Sets & their Application to Clustering & Training

Автор: Lazzerini
Название: Fuzzy Sets & their Application to Clustering & Training
ISBN: 0849305896 ISBN-13(EAN): 9780849305894
Издательство: Taylor&Francis
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Цена: 26796.00 р.
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Описание: Fuzzy logic applications allow uncertain or imprecise data to be clustered and analyzed when traditional methods cannot be used. This volume offers an introduction to fuzzy set theory and then progresses through the algorithms and techniques used to manipulate data using fuzzy sets, including classification, hierarchy, and cluster structure.

Fuzzy Sets, Rough Sets, Multisets and Clustering

Автор: Vicen? Torra; Anders Dahlbom; Yasuo Narukawa
Название: Fuzzy Sets, Rough Sets, Multisets and Clustering
ISBN: 3319475568 ISBN-13(EAN): 9783319475561
Издательство: Springer
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Цена: 20962.00 р.
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Описание: Bringing together contributions by leading researchers in the field, it concretely addresses clustering, multisets, rough sets and fuzzy sets, as well as their applications in areas such as decision-making.The book is divided in four parts, the first of which focuses on clustering and classification.

Statistical Methods for Disease Clustering

Автор: Toshiro Tango
Название: Statistical Methods for Disease Clustering
ISBN: 1461425565 ISBN-13(EAN): 9781461425564
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book offers a modern perspective on statistical methods for detecting disease clustering. It offers analysis and illustration of methods for a variety of real data sets, and will provide an invaluable resource for a wide ranging of audience.

Intelligent Text Categorization and Clustering

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: 20962.00 р.
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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.

Graph Classification And Clustering Based On Vector Space Embedding

Автор: Riesen Kaspar & Bunke Horst
Название: Graph Classification And Clustering Based On Vector Space Embedding
ISBN: 9814304719 ISBN-13(EAN): 9789814304719
Издательство: World Scientific Publishing
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Цена: 17424.00 р.
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Описание: Focuses on a fundamentally novel approach to graph-based pattern recognition based on vector space embedding of graphs. This title aims at condensing the high representational power of graphs into a computationally efficient and mathematically convenient feature vector.


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