Data Clustering

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Data Clustering

Author : Charu C. Aggarwal,Chandan K. Reddy
Publisher : CRC Press
Page : 652 pages
File Size : 43,6 Mb
Release : 2013-08-21
Category : Business & Economics
ISBN : 9781466558229

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Data Clustering by Charu C. Aggarwal,Chandan K. Reddy Pdf

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.

Data Clustering: Theory, Algorithms, and Applications, Second Edition

Author : Guojun Gan,Chaoqun Ma,Jianhong Wu
Publisher : SIAM
Page : 430 pages
File Size : 53,9 Mb
Release : 2020-11-10
Category : Mathematics
ISBN : 9781611976335

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Data Clustering: Theory, Algorithms, and Applications, Second Edition by Guojun Gan,Chaoqun Ma,Jianhong Wu Pdf

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, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.

Data Clustering in C++

Author : Guojun Gan
Publisher : CRC Press
Page : 520 pages
File Size : 44,7 Mb
Release : 2011-03-28
Category : Business & Economics
ISBN : 9781439862247

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Data Clustering in C++ by Guojun Gan Pdf

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,

Model-Based Clustering and Classification for Data Science

Author : Charles Bouveyron,Gilles Celeux,T. Brendan Murphy,Adrian E. Raftery
Publisher : Cambridge University Press
Page : 446 pages
File Size : 44,5 Mb
Release : 2019-07-25
Category : Business & Economics
ISBN : 9781108494205

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Model-Based Clustering and Classification for Data Science by Charles Bouveyron,Gilles Celeux,T. Brendan Murphy,Adrian E. Raftery Pdf

Colorful example-rich introduction to the state-of-the-art for students in data science, as well as researchers and practitioners.

Clustering

Author : Rui Xu,Don Wunsch
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 47,6 Mb
Release : 2008-11-03
Category : Mathematics
ISBN : 9780470382783

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Clustering by Rui Xu,Don Wunsch Pdf

This is the first book to take a truly comprehensive look at clustering. It begins with an introduction to cluster analysis and goes on to explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential data clustering; large-scale data clustering; data visualization and high-dimensional data clustering; and cluster validation. The authors assume no previous background in clustering and their generous inclusion of examples and references help make the subject matter comprehensible for readers of varying levels and backgrounds.

Cluster Analysis for Data Mining and System Identification

Author : János Abonyi,Balázs Feil
Publisher : Springer Science & Business Media
Page : 317 pages
File Size : 41,8 Mb
Release : 2007-08-10
Category : Mathematics
ISBN : 9783764379889

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Cluster Analysis for Data Mining and System Identification by János Abonyi,Balázs Feil Pdf

The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.

Classification, Clustering, and Data Mining Applications

Author : International Federation of Classification Societies. Conference
Publisher : Springer Science & Business Media
Page : 676 pages
File Size : 40,8 Mb
Release : 2004-06-09
Category : Computers
ISBN : 9783540220145

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Classification, Clustering, and Data Mining Applications by International Federation of Classification Societies. Conference Pdf

Modern data analysis stands at the interface of statistics, computer science, and discrete mathematics. This volume describes new methods in this area, with special emphasis on classification and cluster analysis. Those methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.

Data Clustering

Author : Charu C. Aggarwal,Chandan K. Reddy
Publisher : CRC Press
Page : 654 pages
File Size : 46,6 Mb
Release : 2018-09-03
Category : Business & Economics
ISBN : 9781315360416

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Data Clustering by Charu C. Aggarwal,Chandan K. Reddy Pdf

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.

Finding Groups in Data

Author : Leonard Kaufman,Peter J. Rousseeuw
Publisher : Wiley-Interscience
Page : 376 pages
File Size : 45,9 Mb
Release : 1990-03-22
Category : Mathematics
ISBN : UCSD:31822005118112

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Finding Groups in Data by Leonard Kaufman,Peter J. Rousseeuw Pdf

Partitioning around medoids (Program PAM). Clustering large applications (Program CLARA). Fuzzy analysis (Program FANNY). Agglomerative Nesting (Program AGNES). Divisive analysis (Program DIANA). Monothetic analysis (Program MONA). Appendix.

Clustering Methods for Big Data Analytics

Author : Olfa Nasraoui,Chiheb-Eddine Ben N'Cir
Publisher : Springer
Page : 187 pages
File Size : 49,5 Mb
Release : 2018-10-27
Category : Technology & Engineering
ISBN : 9783319978642

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Clustering Methods for Big Data Analytics by Olfa Nasraoui,Chiheb-Eddine Ben N'Cir Pdf

This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

Advances in K-means Clustering

Author : Junjie Wu
Publisher : Springer Science & Business Media
Page : 187 pages
File Size : 53,7 Mb
Release : 2012-07-09
Category : Computers
ISBN : 9783642298073

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Advances in K-means Clustering by Junjie Wu Pdf

Nearly everyone knows K-means algorithm in the fields of data mining and business intelligence. But the ever-emerging data with extremely complicated characteristics bring new challenges to this "old" algorithm. This book addresses these challenges and makes novel contributions in establishing theoretical frameworks for K-means distances and K-means based consensus clustering, identifying the "dangerous" uniform effect and zero-value dilemma of K-means, adapting right measures for cluster validity, and integrating K-means with SVMs for rare class analysis. This book not only enriches the clustering and optimization theories, but also provides good guidance for the practical use of K-means, especially for important tasks such as network intrusion detection and credit fraud prediction. The thesis on which this book is based has won the "2010 National Excellent Doctoral Dissertation Award", the highest honor for not more than 100 PhD theses per year in China.

Grouping Multidimensional Data

Author : Jacob Kogan,Charles Nicholas
Publisher : Taylor & Francis
Page : 296 pages
File Size : 40,9 Mb
Release : 2006-02-10
Category : Computers
ISBN : 354028348X

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Grouping Multidimensional Data by Jacob Kogan,Charles Nicholas Pdf

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Data Clustering

Author : Guojun Gan,Chaoqun Ma,Jianhong Wu
Publisher : SIAM
Page : 471 pages
File Size : 45,5 Mb
Release : 2007-07-12
Category : Mathematics
ISBN : 9780898716238

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Data Clustering by Guojun Gan,Chaoqun Ma,Jianhong Wu Pdf

Reference and compendium of algorithms for pattern recognition, data mining and statistical computing.

Recent Advances in Hybrid Metaheuristics for Data Clustering

Author : Sourav De,Sandip Dey,Siddhartha Bhattacharyya
Publisher : John Wiley & Sons
Page : 196 pages
File Size : 41,8 Mb
Release : 2020-08-24
Category : Computers
ISBN : 9781119551591

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Recent Advances in Hybrid Metaheuristics for Data Clustering by Sourav De,Sandip Dey,Siddhartha Bhattacharyya Pdf

An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics and their application to data clustering. Metaheuristics are designed to tackle complex clustering problems where classical clustering algorithms have failed to be either effective or efficient. The authors—noted experts on the topic—provide a text that can aid in the design and development of hybrid metaheuristics to be applied to data clustering. The book includes performance analysis of the hybrid metaheuristics in relationship to their conventional counterparts. In addition to providing a review of data clustering, the authors include in-depth analysis of different optimization algorithms. The text offers a step-by-step guide in the build-up of hybrid metaheuristics and to enhance comprehension. In addition, the book contains a range of real-life case studies and their applications. This important text: Includes performance analysis of the hybrid metaheuristics as related to their conventional counterparts Offers an in-depth analysis of a range of optimization algorithms Highlights a review of data clustering Contains a detailed overview of different standard metaheuristics in current use Presents a step-by-step guide to the build-up of hybrid metaheuristics Offers real-life case studies and applications Written for researchers, students and academics in computer science, mathematics, and engineering, Recent Advances in Hybrid Metaheuristics for Data Clustering provides a text that explores the current data clustering approaches using a range of computational intelligence techniques.

Classification, Clustering, and Data Analysis

Author : Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock
Publisher : Springer Science & Business Media
Page : 468 pages
File Size : 51,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9783642561818

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Classification, Clustering, and Data Analysis by Krzystof Jajuga,Andrzej Sokolowski,Hans-Hermann Bock Pdf

The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as for applied statisticians and will support the fast transfer of new methodological advances to a wide range of applications.