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Advanced Studies in Classification and Data Science, Imaizumi Tadashi, Okada Akinori, Miyamoto Sadaaki


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Автор: Imaizumi Tadashi, Okada Akinori, Miyamoto Sadaaki
Название:  Advanced Studies in Classification and Data Science
ISBN: 9789811533105
Издательство: Springer
Классификация:



ISBN-10: 9811533105
Обложка/Формат: Paperback
Страницы: 524
Вес: 0.74 кг.
Дата издания: 08.11.2020
Серия: Studies in classification, data analysis, and knowledge organization
Язык: English
Издание: 1st ed. 2020
Иллюстрации: 64 illustrations, color; 57 illustrations, black and white; xi, 524 p. 121 illus., 64 illus. in color.
Размер: 23.39 x 15.60 x 2.77 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
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 DistanceMeasures.- 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 Malvestutos 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 Womens 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 Worlds Population Census Data.- Chapter 40. A Supervised Multiclass Classifieras an Autocoding System for the Family Income and Expenditure Survey.-


Engineering Mathematics II: Algebraic, Stochastic and Analysis Structures for Networks, Data Classification and Optimization

Автор: Silvestrov Sergei, Rančic Milica
Название: Engineering Mathematics II: Algebraic, Stochastic and Analysis Structures for Networks, Data Classification and Optimization
ISBN: 3319824996 ISBN-13(EAN): 9783319824994
Издательство: Springer
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Цена: 20962.00 р.
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Описание:

1 Classification of Low Dimensional 3-Lie Superalgebras: V. Abramov and P. Lдtt.- 2 Semi-Commutative Galois Extension and Reduced Quantum Plane: V. Abramov and Md. Raknuzzaman.- 3 Valued Custom Skew Fields with Generalised PBW Property from Power Series Construction: L. Hellstrцm.- 4 Computing Burchnall-Chaundy Polynomials with Determinants: J. Richter and S. Silvestrov.- 5 Centralizers and Pseudo-Degree Functions: J. Richter.- 6 Asymptotic Expansions for Moment Functionals of Perturbed Discrete Time Semi-Markov Processes: M. Petersson.- 7 Asymptotics for Quasi-Stationary Distributions of Perturbed Discrete Time Semi-Markov Processes: M. Petersson.- 8 PageRank, a Look at Small Changes in a Line of Nodes and the Complete Graph: Ch. Engstrцm and S. Silvestrov.- 9 PageRank, Connecting a Line of Nodes with a Complete Graph: Ch. Engstrцm and S. Silvestrov.- 10 Output Rate Variation Problem: Some Heuristic Paradigms and Dynamic Programming: G.B. Thapa and S. Silvestrov.- 11 Lp-Boundedness of Two Singular Integral Operators of Convolution Type: J. Musonda and S. Kaijser.- 12 Crossed Product Algebras for Piece-Wise Constant Functions: A.B. Tumwesigye et al.- 13 Linear Classification of Data with Support Vector Machines and Generalized Support Vector Machines: Xiaomin Qi et al.- 14 Linear and Nonlinear Classifiers of Data with Support Vector Machines and Generalized Support Vector Machines: X. Qi et al.- 15 Common Fixed Points of Weakly Commuting Multivalued Mappings on a Domain of Sets Endowed with Directed Graph: S. Silvestrov and T. Nazir.- 16 Common Fixed Point Results for Family of Generalized Multivalued F-contraction Mappings in Ordered Metric Spaces: T. Nazir and S. Silvestrov.

Classification and Data Analysis: Theory and Applications

Автор: Jajuga Krzysztof, Batуg Jacek, Walesiak Marek
Название: Classification and Data Analysis: Theory and Applications
ISBN: 3030523470 ISBN-13(EAN): 9783030523473
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This volume gathers peer-reviewed contributions on data analysis, classification and related areas presented at the 28th Conference of the Section on Classification and Data Analysis of the Polish Statistical Association, SKAD 2019, held in Szczecin, Poland, on September 18-20, 2019.

Using classification and regression trees

Автор: Ma, Xin
Название: Using classification and regression trees
ISBN: 1641132388 ISBN-13(EAN): 9781641132381
Издательство: Mare Nostrum (Eurospan)
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Цена: 14137.00 р.
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Описание: Classification and regression trees (CART) is one of the several contemporary statistical techniques with good promise for research in many academic fields. There are very few books on CART, especially on applied CART.This book, as a good practical primer with a focus on applications, introduces the relatively new statistical technique of CART as a powerful analytical tool. The easy-to-understand (non-technical) language and illustrative graphs (tables) as well as the use of the popular statistical software program (SPSS) appeal to readers without strong statistical background. This book helps readers understand the foundation, the operation, and the interpretation of CART analysis, thus becoming knowledgeable consumers and skillful users of CART.The chapter on advanced CART procedures not yet well-discussed in the literature allows readers to effectively seek further empowerment of their research designs by extending the analytical power of CART to a whole new level. This highly practical book is specifically written for academic researchers, data analysts, and graduate students in many disciplines such as economics, social sciences, medical sciences, and sport sciences who do not have strong statistical background but still strive to take full advantage of CART as a powerful analytical tool for research in their fields.

Selected Contributions in Data Analysis and Classification

Автор: Paula Brito; Patrice Bertrand; Guy Cucumel; Franci
Название: Selected Contributions in Data Analysis and Classification
ISBN: 3540735585 ISBN-13(EAN): 9783540735588
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Presents methodological developments in data analysis and classification. This work covers topics including, methods for classification and clustering, dissimilarity analysis, graph analysis, consensus methods, conceptual analysis of data, analysis of symbolic data, data mining, and knowledge discovery in databases.

Cooperation in Classification and Data Analysis

Автор: Akinori Okada; Tadashi Imaizumi; Hans-Hermann Bock
Название: Cooperation in Classification and Data Analysis
ISBN: 3642006671 ISBN-13(EAN): 9783642006678
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Presents theories, models, algorithms, and applications in clustering, classification, and visualization. This work includes applications of clustering, classification, and visualization in various fields such as marketing, recommendation system, biology, sociology, and social survey.

Data Analysis and Classification

Автор: Francesco Palumbo; Carlo Natale Lauro; Michael Gre
Название: Data Analysis and Classification
ISBN: 3642037380 ISBN-13(EAN): 9783642037382
Издательство: Springer
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Цена: 23058.00 р.
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Classification Methodology for Symbolic Data

Автор: Billard
Название: Classification Methodology for Symbolic Data
ISBN: 0470713933 ISBN-13(EAN): 9780470713938
Издательство: Wiley
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Цена: 10446.00 р.
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Описание: Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical methods do not have the power or flexibility to make sense of very large datasets, and symbolic data analysis techniques have been developed in order to extract knowledge from such a data.

Classification, (Big) Data Analysis and Statistical Learning

Автор: Francesco Mola; Claudio Conversano; Maurizio Vichi
Название: Classification, (Big) Data Analysis and Statistical Learning
ISBN: 3319557076 ISBN-13(EAN): 9783319557076
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This edited book focuses on the latest developments in classification, statistical learning, data analysis and related areas of data science, including statistical analysis of large datasets, big data analytics, time series clustering, integration of data from different sources, as well as social networks. It covers both methodological aspects as well as applications to a wide range of areas such as economics, marketing, education, social sciences, medicine, environmental sciences and the pharmaceutical industry. In addition, it describes the basic features of the software behind the data analysis results, and provides links to the corresponding codes and data sets where necessary. This book is intended for researchers and practitioners who are interested in the latest developments and applications in the field. The peer-reviewed contributions were presented at the 10th Scientific Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, held in Santa Margherita di Pula (Cagliari), Italy, October 8–10, 2015.

Classification, Data Analysis, and Knowledge Organization

Автор: Hans-Hermann Bock; Peter Ihm
Название: Classification, Data Analysis, and Knowledge Organization
ISBN: 3540534830 ISBN-13(EAN): 9783540534839
Издательство: Springer
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Цена: 12157.00 р.
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Описание: Proceedings of the 14th Annual Conference of the Gesellschaft fur Klassifikation e.V., University of Marburg March 12-14, 1990

Advances in Classification and Data Analysis

Автор: Simone Borra; Roberto Rocci; Maurizio Vichi; Marti
Название: Advances in Classification and Data Analysis
ISBN: 3540414886 ISBN-13(EAN): 9783540414889
Издательство: Springer
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Цена: 18167.00 р.
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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.

Data Science, Classification, and Related Methods

Автор: Chikio Hayashi; Keiji Yajima; Hans H. Bock; Noboru
Название: Data Science, Classification, and Related Methods
ISBN: 4431702083 ISBN-13(EAN): 9784431702085
Издательство: Springer
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Цена: 12157.00 р.
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Описание: This volume contains selected papers covering a wide range of topics, including theoretical and methodological advances relating to data gathering, classification and clustering, exploratory and multivariate data analysis, and knowledge seeking and discovery.

New Approaches in Classification and Data Analysis

Автор: Edwin Diday; Yves Lechevallier; Martin Schader; Pa
Название: New Approaches in Classification and Data Analysis
ISBN: 3540584250 ISBN-13(EAN): 9783540584254
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This volume describes the analysis and processing of structural or quantitative data. It emphasizes classification methods and new algorithms, as well as applications in various related fields. It consists of survey papers in addition to research results.


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