Finding Groups in Data

An Introduction to Cluster Analysis

Author: Leonard Kaufman,Peter J. Rousseeuw

Publisher: Wiley-Interscience

ISBN: N.A

Category: Mathematics

Page: 342

View: 9533

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The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well." —Mathematical Reviews "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature." —Journal of Classification "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study." —Technometrics An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book discusses various types of data, including interval-scaled and binary variables as well as similarity data, and explains how these can be transformed prior to clustering.
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Cluster Analysis

Author: Brian S. Everitt,Sabine Landau,Morven Leese,Daniel Stahl

Publisher: John Wiley & Sons

ISBN: 9780470978443

Category: Mathematics

Page: 346

View: 9487

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Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics. This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis. Key Features: Presents a comprehensive guide to clustering techniques, with focus on the practical aspects of cluster analysis Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies./li> Updates the chapter on mixture models to include recent developments and presents a new chapter on mixture modeling for structured data Practitioners and researchers working in cluster analysis and data analysis will benefit from this book.
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Handbook of Cluster Analysis

Author: Christian Hennig,Marina Meila,Fionn Murtagh,Roberto Rocci

Publisher: CRC Press

ISBN: 1466551895

Category: Business & Economics

Page: 753

View: 4474

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Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools. The book is organized according to the traditional core approaches to cluster analysis, from the origins to recent developments. After an overview of approaches and a quick journey through the history of cluster analysis, the book focuses on the four major approaches to cluster analysis. These approaches include methods for optimizing an objective function that describes how well data is grouped around centroids, dissimilarity-based methods, mixture models and partitioning models, and clustering methods inspired by nonparametric density estimation. The book also describes additional approaches to cluster analysis, including constrained and semi-supervised clustering, and explores other relevant issues, such as evaluating the quality of a cluster. This handbook is accessible to readers from various disciplines, reflecting the interdisciplinary nature of cluster analysis. For those already experienced with cluster analysis, the book offers a broad and structured overview. For newcomers to the field, it presents an introduction to key issues. For researchers who are temporarily or marginally involved with cluster analysis problems, the book gives enough algorithmic and practical details to facilitate working knowledge of specific clustering areas.
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Marketing Research with IBM® SPSS Statistics

A Practical Guide

Author: Karine Charry,Kristof Coussement,Nathalie Demoulin,Nico Heuvinck

Publisher: Routledge

ISBN: 1315525526

Category: Business & Economics

Page: 250

View: 4543

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Marketing researchers, companies and business schools need to be able to use statistical procedures correctly and accurately interpret the outputs, yet generally these people are scared off by the statistics behind the different analyses procedures, thus they often rely on external sources to come up with profound answers to the proposed research questions. In an accessible and step by step approach, the authors show readers which procedures to use in which particular situation and how to practically execute them using IBM® SPSS Statistics. IBM® is one of the largest statistical software providers world-wide and their IBM® SPSS Statistics software offers a very user-friendly environment. The program uses a simple drag-and-drop menu interface, which is also suitable for non-experienced programmers. It is widely employed in companies and many business schools also use this software package. This straightforward, pragmatic reference manual will help: professional marketers who use statistical procedures in in IBM® SPSS Statistics; undergraduate and postgraduate students where marketing research and research methodology are taught; all researchers analyzing survey-based data in a wide range of frontier domains like psychology, finance, accountancy, negotiation, communication, sociology, criminology, management, information systems, etc. IBM®'s next-generation business analytic solutions help organizations of all sizes make sense of information in the context of their business. You can uncover insights more quickly and easily from all types of data-even big data-and on multiple platforms and devices. And, with self-service and built-in expertise and intelligence, you have the freedom and confidence to make smarter decisions that better address your business imperatives.
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Partitional Clustering Algorithms

Author: M. Emre Celebi

Publisher: Springer

ISBN: 3319092596

Category: Technology & Engineering

Page: 415

View: 7730

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This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volume is to summarize the state-of-the-art in partitional clustering. The book includes such topics as center-based clustering, competitive learning clustering and density-based clustering. Each chapter is contributed by a leading expert in the field.
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Kundenkenntnis im Handel

Ausprägungen, Herkunft und Wirkungen

Author: Günter Silberer

Publisher: Universitätsverlag Göttingen

ISBN: 3940344672

Category: Commerce

Page: 236

View: 3005

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Die Bedeutung der Kundenkenntnis für den Markterfolg der Anbieter ist unbestritten. Dennoch wissen wir wenig darüber, wie gut die Anbieter ihre Kunden kennen. Dies gilt auch für den Handel. Deshalb befasst sich die hier vorgelegte Publikation mit der Ausprägung der Kundenkenntnis im Handel, aber auch mit den Quellen und Determinanten dieser Kenntnis und mit ihren Auswirkungen auf der Anbieter- und auf der Kundenseite. Beachtung finden alle möglichen Quellen der Kundenkenntnis, vor allem aber die Kundenkontakte. Im Einzelnen werden nicht nur relevante Theorien bemüht, sondern auch erste, differenzierte Forschungsergebnisse zur Ausprägung der Kundenkenntnis, zu den Einflussfaktoren und den Auswirkungen dieser Kenntnis präsentiert. Folgerungen für die künftige Forschung und für das Wissensmanagement im Handel schließen das Werk ab.
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Methods for Statistical Data Analysis of Multivariate Observations

Author: R. Gnanadesikan

Publisher: John Wiley & Sons

ISBN: 1118030923

Category: Mathematics

Page: 384

View: 6384

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A practical guide for multivariate statistical techniques-- nowupdated and revised In recent years, innovations in computer technology and statisticalmethodologies have dramatically altered the landscape ofmultivariate data analysis. This new edition of Methods forStatistical Data Analysis of Multivariate Observations explorescurrent multivariate concepts and techniques while retaining thesame practical focus of its predecessor. It integrates methods anddata-based interpretations relevant to multivariate analysis in away that addresses real-world problems arising in many areas ofinterest. Greatly revised and updated, this Second Edition provides helpfulexamples, graphical orientation, numerous illustrations, and anappendix detailing statistical software, including the S (or Splus)and SAS systems. It also offers * An expanded chapter on cluster analysis that covers advances inpattern recognition * New sections on inputs to clustering algorithms and aids forinterpreting the results of cluster analysis * An exploration of some new techniques of summarization andexposure * New graphical methods for assessing the separations among theeigenvalues of a correlation matrix and for comparing sets ofeigenvectors * Knowledge gained from advances in robust estimation anddistributional models that are slightly broader than themultivariate normal This Second Edition is invaluable for graduate students, appliedstatisticians, engineers, and scientists wishing to usemultivariate techniques in a variety of disciplines.
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Multivariate Observations

Author: George A. F. Seber

Publisher: John Wiley & Sons

ISBN: 9780471691211

Category: Mathematics

Page: 686

View: 2933

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WILEY–INTERSCIENCE PAPERBACK SERIES The Wiley–Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "In recent years many monographs have been published on specialized aspects of multivariate data–analysis on cluster analysis, multidimensional scaling, correspondence analysis, developments of discriminant analysis, graphical methods, classification, and so on. This book is an attempt to review these newer methods together with the classical theory. . . . This one merits two cheers." J. C. Gower, Department of Statistics Rothamsted Experimental Station, Harpenden, U.K. Review in Biometrics, June 1987 Multivariate Observations is a comprehensive sourcebook that treats data–oriented techniques as well as classical methods. Emphasis is on principles rather than mathematical detail, and coverage ranges from the practical problems of graphically representing high–dimensional data to the theoretical problems relating to matrices of random variables. Each chapter serves as a self–contained survey of a specific topic. The book includes many numerical examples and over 1,100 references.
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Methods of Multivariate Analysis

Author: Alvin C. Rencher

Publisher: John Wiley & Sons

ISBN: 0471461725

Category: Mathematics

Page: 738

View: 7426

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Amstat News asked three review editors to rate their topfive favorite books in the September 2003 issue. Methods ofMultivariate Analysis was among those chosen. When measuring several variables on a complex experimental unit,it is often necessary to analyze the variables simultaneously,rather than isolate them and consider them individually.Multivariate analysis enables researchers to explore the jointperformance of such variables and to determine the effect of eachvariable in the presence of the others. The Second Edition of AlvinRencher's Methods of Multivariate Analysis provides studentsof all statistical backgrounds with both the fundamental and moresophisticated skills necessary to master the discipline. To illustrate multivariate applications, the author providesexamples and exercises based on fifty-nine real data sets from awide variety of scientific fields. Rencher takes a "methods"approach to his subject, with an emphasis on how students andpractitioners can employ multivariate analysis in real-lifesituations. The Second Edition contains revised and updatedchapters from the critically acclaimed First Edition as well asbrand-new chapters on: Cluster analysis Multidimensional scaling Correspondence analysis Biplots Each chapter contains exercises, with corresponding answers andhints in the appendix, providing students the opportunity to testand extend their understanding of the subject. Methods ofMultivariate Analysis provides an authoritative reference forstatistics students as well as for practicing scientists andclinicians.
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