An Introduction to Clustering with R, Giordani Paolo, Ferraro Maria Brigida, Martella Francesca
Автор: Joseph K. Blitzstein, Jessica Hwang Название: Introduction to Probability, Second Edition ISBN: 1138369918 ISBN-13(EAN): 9781138369917 Издательство: Taylor&Francis Рейтинг: Цена: 74510.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Assumes one-semester of calculus. "Stories" make distributions (Normal, Binomial, Poisson that are widely-used in statistics) easier to remember, understand. Many books write down formulas without explaining clearly why these particular distributions are important or how they are all connected.
Автор: Thomas Villmann; M. Biehl; Barbara Hammer; Michel Название: Similarity-Based Clustering ISBN: 3642018041 ISBN-13(EAN): 9783642018046 Издательство: Springer Рейтинг: Цена: 95770.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Recent Developments and Biomedical Applications. .
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: James Gareth Название: An Introduction to Statistical Learning ISBN: 1461471370 ISBN-13(EAN): 9781461471370 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Невозможна поставка. Описание: This book presents key modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, and clustering.
Автор: Boris Mirkin Название: Mathematical Classification and Clustering ISBN: 146138057X ISBN-13(EAN): 9781461380573 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina- torial optimization to biology, sociology and organizational structures.
Автор: Lerman Israлl Cйsar Название: Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering ISBN: 1447173929 ISBN-13(EAN): 9781447173922 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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: Collica Randall S. Название: Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition ISBN: 1642953091 ISBN-13(EAN): 9781642953091 Издательство: Неизвестно Рейтинг: Цена: 105390.00 T Наличие на складе: Невозможна поставка. Описание: Understanding your customers is the key to your company's success
Segmentation is one of the first and most basic machine learning methods. It can be used by companies to understand their customers better, boost relevance of marketing messaging, and increase efficacy of predictive models. In Customer Segmentation and Clustering Using SAS Enterprise Miner, Third Edition, Randy Collica explains, in step-by-step fashion, the most commonly available techniques for segmentation using the powerful data mining software SAS Enterprise Miner.
A working guide that uses real-world data, this new edition will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. Step-by-step examples and exercises, using a number of machine learning and data mining techniques, clearly illustrate the concepts of segmentation and clustering in the context of customer relationship management.
The book includes four parts, each of which increases in complexity. Part 1 reviews the basics of segmentation and clustering at an introductory level, providing examples from a variety of industries. Part 2 offers an in-depth treatment of segmentation with practical topics, such as when and how to update your models. Part 3 goes beyond traditional segmentation practices to introduce recommended strategies for clustering product affinities, handling missing data, and incorporating textual records into your predictive model with SAS Text Miner. Finally, part 4 takes segmentation to a new level with advanced techniques, such as clustering of product associations, developing segmentation-scoring models from customer survey data, combining segmentations using ensemble segmentation, and segmentation of customer transactions.
New to the third edition is a chapter that focuses on predictive models within microsegments and combined segments, and a new parallel process technique is introduced using SAS Factory Miner. In addition, all examples have been updated to the latest version of SAS Enterprise Miner.
Автор: Andreopoulou Zacharoula, Koliouska Christiana, Zopounidis Constantin Название: Multicriteria and Clustering: Classification Techniques in Agrifood and Environment ISBN: 3319856960 ISBN-13(EAN): 9783319856964 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Further, it presents some of the most common methodologies for statistical analysis and mathematical modeling, and discusses in detail ten examples that explain and show "hands-on" how operational research can be used in key decision-making processes at enterprises in the agricultural food and environmental industries.
Автор: Gan, Guojun Название: Data Clustering in C++ ISBN: 0367382954 ISBN-13(EAN): 9780367382957 Издательство: Taylor&Francis Рейтинг: Цена: 65320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Data clustering is a highly interdisciplinary field, the goal of which is to divide a set of objects into homogeneous groups such that objects in the same group are similar and objects in different groups are quite distinct. Thousands of theoretical papers and a number of books on data clustering have been published over the past 50 years. However, few books exist to teach people how to implement data clustering algorithms. This book was written for anyone who wants to implement or improve their data clustering algorithms.
Using object-oriented design and programming techniques, Data Clustering in C++ exploits the commonalities of all data clustering algorithms to create a flexible set of reusable classes that simplifies the implementation of any data clustering algorithm. Readers can follow the development of the base data clustering classes and several popular data clustering algorithms. Additional topics such as data pre-processing, data visualization, cluster visualization, and cluster interpretation are briefly covered.
This book is divided into three parts--
Data Clustering and C++ Preliminaries: A review of basic concepts of data clustering, the unified modeling language, object-oriented programming in C++, and design patterns
A C++ Data Clustering Framework: The development of data clustering base classes
Data Clustering Algorithms: The implementation of several popular data clustering algorithms
A key to learning a clustering algorithm is to implement and experiment the clustering algorithm. Complete listings of classes, examples, unit test cases, and GNU configuration files are included in the appendices of this book as well as in the downloadable resources. The only requirements to compile the code are a modern C++ compiler and the Boost C++ libraries.
Автор: Mirkin, Boris Название: Clustering for Data Mining ISBN: 1584885343 ISBN-13(EAN): 9781584885344 Издательство: Taylor&Francis Рейтинг: Цена: 61240.00 T Наличие на складе: Нет в наличии. Описание: Presents a theory that not only closes gaps in K-Means and Ward methods, but also extends them into areas of interest, such as clustering mixed scale data and incomplete clustering. This work suggests methods for both cluster finding and cluster description, and includes nearly 60 computational examples covering the various stages of clustering.
Автор: Chaoqun Ma, Guojun Gan, Jianhong Wu Название: Data Clustering: Theory, Algorithms, and Applications ISBN: 1611976324 ISBN-13(EAN): 9781611976328 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 81090.00 T Наличие на складе: Нет в наличии. Описание: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments.Data Clustering: Theory, Algorithms, and Applications, Second Edition:covers the basics of data clustering,includes a list of popular clustering algorithms, andprovides program code that helps users implement clustering algorithms.
Автор: Maharaj Название: Time Series Clustering And Classifi ISBN: 1498773214 ISBN-13(EAN): 9781498773218 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students.
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