Correlation Clustering: Morgan & Claypool Publishers, Bonchi Francesco, Garcнa-Soriano David, Gullo Francesco

Автор: David GarcIa-Soriano, Francesco Bonchi, Francesco Gullo
Название: Correlation Clustering
ISBN: 163639325X ISBN-13(EAN): 9781636393254
Издательство: Mare Nostrum (Eurospan)
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Цена: 74850.00 T
Наличие на складе: Нет в наличии.
Описание: Despite its simplicity, generality, and wide applicability, correlation clustering has so far received much more attention from an algorithmic-theory perspective than from the data-mining community. This book shows how correlation clustering can be a powerful addition to the toolkit of a data-mining researcher and practitioner.

Автор: Aljarah Ibrahim, Faris Hossam, Mirjalili Seyedali
Название: Evolutionary Data Clustering: Algorithms and Applications
ISBN: 9813341939 ISBN-13(EAN): 9789813341937
Издательство: Springer
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Цена: 167700.00 T
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Описание: It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization.

Автор: Dmitri A. Viattchenin
Название: A Heuristic Approach to Possibilistic Clustering: Algorithms and Applications
ISBN: 364244301X ISBN-13(EAN): 9783642443015
Издательство: Springer
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Цена: 113180.00 T
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Описание: In a new approach to possibilistic clustering, the sought clustering structure of the set is based directly on the formal definition of fuzzy cluster and possibilistic memberships are determined directly from the values of the pairwise similarity of objects.

Автор: Thomas Villmann; M. Biehl; Barbara Hammer; Michel
Название: Similarity-Based Clustering
ISBN: 3642018041 ISBN-13(EAN): 9783642018046
Издательство: Springer
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Цена: 95770.00 T
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Описание: Recent Developments and Biomedical Applications. .

Автор: Mirkin Boris
Название: Core Data Analysis: Summarization, Correlation, and Visualiz
ISBN: 3030002705 ISBN-13(EAN): 9783030002701
Издательство: Springer
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Цена: 60550.00 T
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Описание: This text examines the goals of data analysis with respect to enhancing knowledge, and identifies data summarization and correlation analysis as the core issues. Data summarization, both quantitative and categorical, is treated within the encoder-decoder paradigm bringing forward a number of mathematically supported insights into the methods and relations between them. Two Chapters describe methods for categorical summarization: partitioning, divisive clustering and separate cluster finding and another explain the methods for quantitative summarization, Principal Component Analysis and PageRank. Features:· An in-depth presentation of K-means partitioning including a corresponding Pythagorean decomposition of the data scatter. · Advice regarding such issues as clustering of categorical and mixed scale data, similarity and network data, interpretation aids, anomalous clusters, the number of clusters, etc.· Thorough attention to data-driven modelling including a number of mathematically stated relations between statistical and geometrical concepts including those between goodness-of-fit criteria for decision trees and data standardization, similarity and consensus clustering, modularity clustering and uniform partitioning.New edition highlights: · Inclusion of ranking issues such as Google PageRank, linear stratification and tied rankings median, consensus clustering, semi-average clustering, one-cluster clustering· Restructured to make the logics more straightforward and sections self-containedCore Data Analysis: Summarization, Correlation and Visualization is aimed at those who are eager to participate in developing the field as well as appealing to novices and practitioners.

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
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Цена: 153720.00 T
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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: Philip D. Waggoner
Название: Unsupervised Machine Learning for Clustering in Political and Social Research
ISBN: 110879338X ISBN-13(EAN): 9781108793384
Издательство: Cambridge Academ
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Цена: 19010.00 T
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Описание: Offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered, in addition to R code and real data to facilitate interaction with the concepts.

Автор: Lerman Israлl Cйsar
Название: Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering
ISBN: 1447173929 ISBN-13(EAN): 9781447173922
Издательство: Springer
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Цена: 139750.00 T
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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: Francesco Masulli; Alfredo Petrosino; Stefano Rove
Название: Clustering High--Dimensional Data
ISBN: 3662485761 ISBN-13(EAN): 9783662485767
Издательство: Springer
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Цена: 37270.00 T
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Описание: This book constitutes the proceedings of the International Workshop on Clustering High-Dimensional Data, CHDD 2012, held in Naples, Italy, in May 2012. and the most common approach to tackle dimensionality problems, namely, dimensionality reduction and its application in clustering.

Автор: Jin Cheqing, Zhou Aoying, Mao Jiali
Название: Clustering And Outlier Detection For Trajectory Stream Data
ISBN: 9811210454 ISBN-13(EAN): 9789811210457
Издательство: World Scientific Publishing
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Цена: 95040.00 T
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Описание:

As mobile devices continue becoming a larger part of our lives, the development of location acquisition technologies to track moving objects have focused the minds of researchers on issues ranging from longitude and latitude coordinates, speed, direction, and timestamping, as part of parameters needed to calculate the positional information and locations of objects, in terms of time and position in the form of trajectory streams. Recently, recent advances have facilitated various urban applications such as smart transportation and mobile delivery services.

Unlike other books on spatial databases, mobile computing, data mining, or computing with spatial trajectories, this book is focused on smart transportation applications.

This book is a good reference for advanced undergraduates, graduate students, researchers, and system developers working on transportation systems.

Автор: Aljarah Ibrahim, Faris Hossam, Mirjalili Seyedali
Название: Evolutionary Data Clustering: Algorithms and Applications
ISBN: 9813341904 ISBN-13(EAN): 9789813341906
Издательство: Springer
Цена: 167700.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization.

Автор: V.S. Kumbhar, K.S. Oza, R.K. Kamat
Название: Web Mining: A Synergic Approach Resorting to Classification and Clustering
ISBN: 8793379838 ISBN-13(EAN): 9788793379831
Издательство: Taylor&Francis
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Цена: 73490.00 T
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Описание: Showcases an effective methodology for classification and clustering of web sites from a usability point of view. While the clustering and classification is accomplished by using an open source tool, WEKA, the basic dataset for the selected websites has been arrived at by using a free tool site-analyser. As a case study, several commercial websites are analysed.