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Knowledge Based Clustering
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Book Synopsis Knowledge-Based Clustering by : Witold Pedrycz
Download or read book Knowledge-Based Clustering written by Witold Pedrycz and published by John Wiley & Sons. This book was released on 2005-05-13 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive coverage of emerging and current technology dealing with heterogeneous sources of information, including data, design hints, reinforcement signals from external datasets, and related topics Covers all necessary prerequisites, and if necessary,additional explanations of more advanced topics, to make abstract concepts more tangible Includes illustrative material andwell-known experimentsto offer hands-on experience
Book Synopsis Transcriptome Analysis by : Alessandro Cellerino
Download or read book Transcriptome Analysis written by Alessandro Cellerino and published by Springer. This book was released on 2018-06-14 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The goal of this book is to be an accessible guide for undergraduate and graduate students to the new field of data-driven biology. Next-generation sequencing technologies have put genome-scale analysis of gene expression into the standard toolbox of experimental biologists. Yet, biological interpretation of high-dimensional data is made difficult by the lack of a common language between experimental and data scientists. By combining theory with practical examples of how specific tools were used to obtain novel insights in biology, particularly in the neurosciences, the book intends to teach students how to design, analyse, and extract biological knowledge from transcriptome sequencing experiments. Undergraduate and graduate students in biomedical and quantitative sciences will benefit from this text as well as academics untrained in the subject.
Book Synopsis Model-Based Clustering and Classification for Data Science by : Charles Bouveyron
Download or read book Model-Based Clustering and Classification for Data Science written by Charles Bouveyron and published by Cambridge University Press. This book was released on 2019-07-25 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
Book Synopsis Data Mining and Knowledge Discovery Handbook by : Oded Maimon
Download or read book Data Mining and Knowledge Discovery Handbook written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2006-05-28 with total page 1378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
Book Synopsis Cluster Analysis for Applications by : Michael R. Anderberg
Download or read book Cluster Analysis for Applications written by Michael R. Anderberg and published by Academic Press. This book was released on 2014-05-10 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis. Comprised of 10 chapters, this book begins with an introduction to the subject of cluster analysis and its uses as well as category sorting problems and the need for cluster analysis algorithms. The next three chapters give a detailed account of variables and association measures, with emphasis on strategies for dealing with problems containing variables of mixed types. Subsequent chapters focus on the central techniques of cluster analysis with particular reference to computational considerations; interpretation of clustering results; and techniques and strategies for making the most effective use of cluster analysis. The final chapter suggests an approach for the evaluation of alternative clustering methods. The presentation is capped with a complete set of implementing computer programs listed in the Appendices to make the use of cluster analysis as painless and free of mechanical error as is possible. This monograph is intended for students and workers who have encountered the notion of cluster analysis.
Book Synopsis Data Clustering by : Charu C. Aggarwal
Download or read book Data Clustering written by Charu C. Aggarwal and published by CRC Press. This book was released on 2013-08-21 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Projection-Based Clustering through Self-Organization and Swarm Intelligence by : Michael Christoph Thrun
Download or read book Projection-Based Clustering through Self-Organization and Swarm Intelligence written by Michael Christoph Thrun and published by Springer. This book was released on 2018-01-09 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is published open access under a CC BY 4.0 license. It covers aspects of unsupervised machine learning used for knowledge discovery in data science and introduces a data-driven approach to cluster analysis, the Databionic swarm (DBS). DBS consists of the 3D landscape visualization and clustering of data. The 3D landscape enables 3D printing of high-dimensional data structures. The clustering and number of clusters or an absence of cluster structure are verified by the 3D landscape at a glance. DBS is the first swarm-based technique that shows emergent properties while exploiting concepts of swarm intelligence, self-organization and the Nash equilibrium concept from game theory. It results in the elimination of a global objective function and the setting of parameters. By downloading the R package DBS can be applied to data drawn from diverse research fields and used even by non-professionals in the field of data mining.
Book Synopsis Data Clustering by : Charu C. Aggarwal
Download or read book Data Clustering written by Charu C. Aggarwal and published by CRC Press. This book was released on 2018-09-03 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Knowledge-based Cluster Development by : Amanda Nelson
Download or read book Knowledge-based Cluster Development written by Amanda Nelson and published by . This book was released on 2007 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Knowledge-Based Intelligent Information and Engineering Systems by : Bogdan Gabrys
Download or read book Knowledge-Based Intelligent Information and Engineering Systems written by Bogdan Gabrys and published by Springer. This book was released on 2006-10-11 with total page 1338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The three volume set LNAI 4251, LNAI 4252, and LNAI 4253 constitutes the refereed proceedings of the 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006, held in Bournemouth, UK, in October 2006. The 480 revised papers presented were carefully reviewed and selected from about 1400 submissions. The papers present a wealth of original research results from the field of intelligent information processing.
Book Synopsis Feature and Dimensionality Reduction for Clustering with Deep Learning by : Frederic Ros
Download or read book Feature and Dimensionality Reduction for Clustering with Deep Learning written by Frederic Ros and published by Springer Nature. This book was released on 2024-01-22 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major recent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by “family” to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers.
Book Synopsis Data Clustering in C++ by : Guojun Gan
Download or read book Data Clustering in C++ written by Guojun Gan and published by CRC Press. This book was released on 2011-03-28 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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,
Book Synopsis Industrial Clusters by : John F. Wilson
Download or read book Industrial Clusters written by John F. Wilson and published by Routledge. This book was released on 2022-07-01 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial Clusters shows the latest state of knowledge on the topic of industrial clusters, with a particular focus on clustering in the UK, bringing together a chronological coverage of the phenomenon. This set of original essays by a group of leading business and industrial historians offers fresh perspectives about clusters and clustering. A primary emphasis of the collection is how knowledge is generated and disseminated across a cluster, and whether these processes stimulated innovation and consequently longer-term sustainability. This analysis also prompts questions about which unit of analysis to examine, from the entrepreneurs and firms they created through to the industry as a whole and district in which they are located, or whether one should look outside the region for explanatory factors. Covering regions as diverse as North Wales, the Scottish Highlands, the City of London, the Potteries, Sheffield and Lancashire, the essays have been channelled to provide a detailed understanding of these issues. The editors have also provided a challenging Conclusion that suggests a new research agenda that could well unravel some of the mysteries associated with clustering. This edited collection will be of interest to international researchers, academics and students in the fields of business and management history, innovation, industrialisation and clusters.
Book Synopsis The Mathematics of Inheritance Systems by : David S. Touretzky
Download or read book The Mathematics of Inheritance Systems written by David S. Touretzky and published by Morgan Kaufmann. This book was released on 1986 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Clustering: Theory, Algorithms, and Applications, Second Edition by : Guojun Gan
Download or read book Data Clustering: Theory, Algorithms, and Applications, Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Encyclopedia of Machine Learning by : Claude Sammut
Download or read book Encyclopedia of Machine Learning written by Claude Sammut and published by Springer Science & Business Media. This book was released on 2011-03-28 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.
Book Synopsis Intelligence Methods and Systems Advancements for Knowledge-Based Business by : Wang, John
Download or read book Intelligence Methods and Systems Advancements for Knowledge-Based Business written by Wang, John and published by IGI Global. This book was released on 2012-07-31 with total page 397 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge is power: In todays era of knowledge-based economies, constantly changing business environments, severe competition, and globalization, gaining the knowledge edge will greatly empower an organization to stay on the cutting edge. Intelligence Methods and Systems Advancements for Knowledge-Based Business examines state-of-the-art research in decision sciences and business intelligence, and the applications of knowledge-based business with information systems. This comprehensive volume will provide researchers, academics, and business professionals with the research and inspiration they need to strengthen and empower their businesses in todays world.
