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 Рейтинг: Цена: 89760.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: * In this book, authors Rachev, Kim, Bianchi, and Fabozzi present readers with the notions of risk and their corresponding performance measures.
Автор: Lazzerini Название: Fuzzy Sets & their Application to Clustering & Training ISBN: 0849305896 ISBN-13(EAN): 9780849305894 Издательство: Taylor&Francis Рейтинг: Цена: 178640.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Vicen? Torra; Anders Dahlbom; Yasuo Narukawa Название: Fuzzy Sets, Rough Sets, Multisets and Clustering ISBN: 3319475568 ISBN-13(EAN): 9783319475561 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Toshiro Tango Название: Statistical Methods for Disease Clustering ISBN: 1461425565 ISBN-13(EAN): 9781461425564 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Felipe M. G. Fran?a; Alberto Ferreira de Souza Название: Intelligent Text Categorization and Clustering ISBN: 3540856439 ISBN-13(EAN): 9783540856436 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: Guojun Gan Название: Data Clustering: Theory, Algorithms, and Applications ISBN: 0898716233 ISBN-13(EAN): 9780898716238 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 112860.00 T Наличие на складе: Невозможна поставка. 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: Riesen Kaspar & Bunke Horst Название: Graph Classification And Clustering Based On Vector Space Embedding ISBN: 9814304719 ISBN-13(EAN): 9789814304719 Издательство: World Scientific Publishing Рейтинг: Цена: 116160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Alexander Bolshoy; Zeev Volkovich; Valery Kirzhner Название: Genome Clustering ISBN: 3642263402 ISBN-13(EAN): 9783642263408 Издательство: Springer Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
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