Model-Based Clustering, Classification, and Density Estimation Using mclust in R, Scrucca, Luca
Автор: Scrucca, Luca Fraley, Chris Murphy, T. Brendan Adrian E., Raftery Название: Model-based clustering, classification, and density estimation using mclust in r ISBN: 1032234954 ISBN-13(EAN): 9781032234953 Издательство: Taylor&Francis Рейтинг: Цена: 54090.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling.
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: Maharaj, Elizabeth Ann Название: Time Series Clustering and Classification ISBN: 1032093498 ISBN-13(EAN): 9781032093499 Издательство: Taylor&Francis Рейтинг: Цена: 48990.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Zacharoula Andreopoulou; Christiana Koliouska; Con Название: Multicriteria and Clustering ISBN: 3319555642 ISBN-13(EAN): 9783319555645 Издательство: Springer Рейтинг: Цена: 83850.00 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: Francesco Palumbo; Angela Montanari; Maurizio Vich Название: Data Science ISBN: 331955722X ISBN-13(EAN): 9783319557229 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications.
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: 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: Giordani Paolo, Ferraro Maria Brigida, Martella Francesca Название: An Introduction to Clustering with R ISBN: 9811305528 ISBN-13(EAN): 9789811305528 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The purpose of this book is to thoroughly prepare the reader for applied research in clustering. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses.
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: Поставка под заказ. 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: Isra?l C?sar Lerman Название: Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering ISBN: 1447167910 ISBN-13(EAN): 9781447167914 Издательство: Springer Рейтинг: Цена: 153720.00 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: 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
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