Автор: David G. T. Denison Название: Bayesian Methods for Nonlinear Classification and Regression ISBN: 0471490369 ISBN-13(EAN): 9780471490364 Издательство: Wiley Рейтинг: Цена: 20584.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Regression analysis models the relationship between a set of responses and another variable: for example, to estimate the true position of a line through a number of observed points. Unfortunately, data rarely conforms to simple curves and straight lines - parametric models - and this text examines more complex - or nonparametric - models.
Автор: Hans-Hermann Bock; Peter Ihm Название: Classification, Data Analysis, and Knowledge Organization ISBN: 3540534830 ISBN-13(EAN): 9783540534839 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of the 14th Annual Conference of the Gesellschaft fur Klassifikation e.V., University of Marburg March 12-14, 1990
Автор: Simone Borra; Roberto Rocci; Maurizio Vichi; Marti Название: Advances in Classification and Data Analysis ISBN: 3540414886 ISBN-13(EAN): 9783540414889 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents developments in classification and mulitivariate analysis. Topics that have been treated with considerable attention include cluster analysis, discriminant analysis, proximity structure analysis, multidimensional scaling, genetic algorithms, and neural networks.
Автор: David D. Denison; Mark H. Hansen; Christopher C. H Название: Nonlinear Estimation and Classification ISBN: 0387954716 ISBN-13(EAN): 9780387954714 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing.
Автор: Bernard van Cutsem Название: Classification and Dissimilarity Analysis ISBN: 0387944001 ISBN-13(EAN): 9780387944005 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Classifying objects according to their likeness seems to have been a step in the human process of acquiring knowledge, and it is certainly a basic part of many of the sciences. Thus, classification is close to factorial analysis methods and to multi-dimensional scaling methods.
Описание: The search for neutrinoless double beta decay is one of the highest priority areas in particle physics today; it could provide insights to the nature of neutrino masses (currently not explained by the Standard Model) as well as how the universe survived its early stages. One promising experimental approach involves the use of large volumes of isotope-loaded liquid scintillator, but new techniques for background identification and suppression must be developed in order to reach the required sensitivity levels and clearly distinguish the signal. The results from this thesis constitute a significant advance in this area, laying the groundwork for several highly effective and novel approaches based on a detailed evaluation of state-of-the-art detector characteristics. This well written thesis includes a particularly clear and comprehensive description of the theoretical motivations as well as impressively demonstrating the effective use of diverse statistical techniques. The professionally constructed signal extraction framework contains clever algorithmic solutions to efficient error propagation in multi-dimensional space. In general, the techniques developed in this work will have a notable impact on the field.
Описание: This book describes statistical techniques for the design and evaluation of research studies on medical diagnostic tests, screening tests, biomarkers and new technologies for classification and prediction in medicine.
Автор: Gordon, A.D. Название: Classification ISBN: 0367399660 ISBN-13(EAN): 9780367399665 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
As the amount of information recorded and stored electronically grows ever larger, it becomes increasingly useful, if not essential, to develop better and more efficient ways to summarize and extract information from these large, multivariate data sets. The field of classification does just that-investigates sets of objects to see if they can be summarized into a small number of classes comprising similar objects. Researchers have made great strides in the field over the last twenty years, and classification is no longer perceived as being concerned solely with exploratory analyses. The second edition of Classification incorporates many of the new and powerful methodologies developed since its first edition. Like its predecessor, this edition describes both clustering and graphical methods of representing data, and offers advice on how to decide which methods of analysis best apply to a particular data set. It goes even further, however, by providing critical overviews of recent developments not widely known, including efficient clustering algorithms, cluster validation, consensus classifications, and the classification of symbolic data. The author has taken an approach accessible to researchers in the wide variety of disciplines that can benefit from classification analysis and methods. He illustrates the methodologies by applying them to data sets-smaller sets given in the text, larger ones available through a Web site. Large multivariate data sets can be difficult to comprehend-the sheer volume and complexity can prove overwhelming. Classification methods provide efficient, accurate ways to make them less unwieldy and extract more information. Classification, Second Edition offers the ideal vehicle for gaining the background and learning the methodologies-and begin putting these techniques to use.
Автор: Otto Opitz; Berthold Lausen; R?diger Klar Название: Information and Classification ISBN: 3540567364 ISBN-13(EAN): 9783540567363 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In many fields of science and practice large amounts of dataand informationare collected for analyzing and visualizinglatent structures as orderings or classifications forexample. So, in the first sectionwe find papers on Classification Methods, FuzzyClassification, Multidimensional Scaling, DiscriminantAnalysis and Conceptual Analysis.
Автор: Wolfgang A. Gaul; Dietmar Pfeifer Название: From Data to Knowledge ISBN: 3540603549 ISBN-13(EAN): 9783540603542 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The subject of this work is the incorporation and integration of mathematical and statistical techniques, and information science topics into the field of classification, data analysis, and knowledge organization.
Автор: Imaizumi Tadashi, Okada Akinori, Miyamoto Sadaaki Название: Advanced Studies in Classification and Data Science ISBN: 9811533105 ISBN-13(EAN): 9789811533105 Издательство: Springer Рейтинг: Цена: 30745.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 1. Multilevel model-based clustering: A new proposal of maximum-a-posteriori assignment.- Chapter 2. Multi-citeria classifications in regional development modelling.- Chapter 3. Non-parametric latent modeling and network clustering.- Chapter 4. Efficient, Geometrically-adaptive Techniques for Multiscale Gaussian-kernel SVM Classification.- Chapter 5. Random forests followed by computed ABC analysis as a feature selection method for machine-learning in biomedical data.- Chapter 6. Non-Hierarchical Clustering for Large Data without Recalculating Cluster Center.- Chapter 7. Supervised Nested Algorithm for Classification based on K-means.- Chapter 8. Using Classification of Regions Based on the Complexity of the Global Progress Indices for Supporting Development in Competitiveness.- Chapter 9. Estimation Methods Based on Weighting Clusters.- Chapter 10. Five Strategies for Accommodating Overdispersion in Simple Correspondence Analysis.- Chapter 11. From Joint Graphical Display to Bi-Modal Clustering: [2] Dual Space Versus Total Space.- Chapter 12. Linear Time Visualization and Search in Big Data using Pixellated Factor Space Mapping.- Chapter 13. From Joint Graphical Display to Bi-Modal Clustering: [1] A Giant Leap in Quantication Theory.- Chapter 14. External Logistic Biplots for Mixed Types of Data.- Chapter 15. Functional clustering approach for analysis of concentration.- Chapter 16. Generalized additive models for the detection of copy number variations (CNVs) using multi gene panel sequencing data.- Chapter 17. Variable selection for classification of multivariate functional data.- Chapter 18. Initial value selection for the alternating least squares algorithm.- Chapter 19. Inference for General MANOVA Based on ANOVA-Type Statistic.- Chapter 20. How To Cross the River? - New 'Distance'Measures.- Chapter 21. New Statistical Matching Method Using Multinomial Logistic Regression Model.- Chapter 22. Constructing graphical models for multi-source data: Sparse Network And Component analysis.- Chapter 23. Understanding Malvestuto's normalized mutual information.- Chapter 24. Understanding the Rand index.- Chapter 25. Layered Multivariate Regression with Its Applications.- Chapter 26. An exploratory study on the clumpiness measure of intertransaction times: how is it useful for customer relationship management?.- Chapter 27. Data Quality Management of Chain Stores based on Outlier Detection.- Chapter 28. Analysis of expenditure pattens of virtual marriage households consisting of working couples synthesized by statistical matching method q.- Chapter 29. The Effects of Natural Disasters on Household Income and Poverty in Rural Vietnam: An Analysis Using the Vietnam Household Living Standards Survey.- Chapter 30. Generalizability of relationship between number of tweets about and sales of new beverage products.- Chapter 31. Cluster Distance-Based Regression.- Chapter 32. Bayesian network analysis of fashion behaviour.- Chapter 33. Determining the Similarity Index in Electoral Behavior Analysis: An Issue Voting Behavioral: Mapping.- Chapter 34. Well-Being Measures.- Chapter 35. The Relationship between Household Assets and Choice to Work: Evidence from Japanese Official Microdata.- Chapter 36. Visualization and Spatial Statistical Analysis for Vietnam Household Living Standard Survey.- Chapter 37. Changes in the Gendered Division of Labor and Women's Economic Contributions within Japanese Couples.- Chapter 38. Employment structures vs. educational capital in the European Union regions.- Chapter 39. The IPUMS Approach to Harmonizing the World's Population Census Data.- Chapter 40. A Supervised Multiclass Classifieras an Autocoding System for the Family Income and Expenditure Survey.-
Автор: Nadja Bauer; Katja Ickstadt; Karsten L?bke; Gero S Название: Applications in Statistical Computing ISBN: 3030251462 ISBN-13(EAN): 9783030251468 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.
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