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: 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: 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: Gan, Guojun Название: Data Clustering in C++ ISBN: 1439862230 ISBN-13(EAN): 9781439862230 Издательство: Taylor&Francis Рейтинг: Цена: 148010.00 T Наличие на складе: Нет в наличии.
Автор: Junjie Wu Название: Advances in K-means Clustering ISBN: 3642447570 ISBN-13(EAN): 9783642447570 Издательство: Springer Рейтинг: Цена: 102480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The K-means algorithm is commonly used in data mining and business intelligence. This award-winning research pioneers its application to the intricacies of `big data`, detailing a theoretical framework for aggregating and validating clusters with K-means.
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.
Автор: Jacob Kogan; Charles Nicholas; Marc Teboulle Название: Grouping Multidimensional Data ISBN: 3642066542 ISBN-13(EAN): 9783642066542 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Clustering can be used as an independent data mining task to discern intrinsic characteristics of data, or as a preprocessing step with the clustering results then used for classification, correlation analysis, or anomaly detection.Kogan and his co-editors have put together recent advances in clustering large and high-dimension data.
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: 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: Francesco Название: Correlation Clustering ISBN: 3031791983 ISBN-13(EAN): 9783031791987 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Given a set of objects and a pairwise similarity measure between them, the goal of correlation clustering is to partition the objects in a set of clusters to maximize the similarity of the objects within the same cluster and minimize the similarity of the objects in different clusters.
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