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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 Synopsis Handbook of Cluster Analysis by : Christian Hennig
Download or read book Handbook of Cluster Analysis written by Christian Hennig and published by CRC Press. This book was released on 2015-12-16 with total page 753 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Although there are several good books on unsupervised machine learning, we felt that many of them are too theoretical. This book provides practical guide to cluster analysis, elegant visualization and interpretation. It contains 5 parts. Part I provides a quick introduction to R and presents required R packages, as well as, data formats and dissimilarity measures for cluster analysis and visualization. Part II covers partitioning clustering methods, which subdivide the data sets into a set of k groups, where k is the number of groups pre-specified by the analyst. Partitioning clustering approaches include: K-means, K-Medoids (PAM) and CLARA algorithms. In Part III, we consider hierarchical clustering method, which is an alternative approach to partitioning clustering. The result of hierarchical clustering is a tree-based representation of the objects called dendrogram. In this part, we describe how to compute, visualize, interpret and compare dendrograms. Part IV describes clustering validation and evaluation strategies, which consists of measuring the goodness of clustering results. Among the chapters covered here, there are: Assessing clustering tendency, Determining the optimal number of clusters, Cluster validation statistics, Choosing the best clustering algorithms and Computing p-value for hierarchical clustering. Part V presents advanced clustering methods, including: Hierarchical k-means clustering, Fuzzy clustering, Model-based clustering and Density-based clustering.
Book Synopsis Practical Guide to Cluster Analysis in R by : Alboukadel Kassambara
Download or read book Practical Guide to Cluster Analysis in R written by Alboukadel Kassambara and published by STHDA. This book was released on 2017-08-23 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although there are several good books on unsupervised machine learning, we felt that many of them are too theoretical. This book provides practical guide to cluster analysis, elegant visualization and interpretation. It contains 5 parts. Part I provides a quick introduction to R and presents required R packages, as well as, data formats and dissimilarity measures for cluster analysis and visualization. Part II covers partitioning clustering methods, which subdivide the data sets into a set of k groups, where k is the number of groups pre-specified by the analyst. Partitioning clustering approaches include: K-means, K-Medoids (PAM) and CLARA algorithms. In Part III, we consider hierarchical clustering method, which is an alternative approach to partitioning clustering. The result of hierarchical clustering is a tree-based representation of the objects called dendrogram. In this part, we describe how to compute, visualize, interpret and compare dendrograms. Part IV describes clustering validation and evaluation strategies, which consists of measuring the goodness of clustering results. Among the chapters covered here, there are: Assessing clustering tendency, Determining the optimal number of clusters, Cluster validation statistics, Choosing the best clustering algorithms and Computing p-value for hierarchical clustering. Part V presents advanced clustering methods, including: Hierarchical k-means clustering, Fuzzy clustering, Model-based clustering and Density-based clustering.
Book Synopsis Cluster Analysis by : Brian S. Everitt
Download or read book Cluster Analysis written by Brian S. Everitt and published by . This book was released on 1977 with total page 122 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Karlsson has assembled a strong mix of papers that collectively provide a good sense of some of the latest research in the field. Edward Feser, Review of Regional Studies This is a book every regional scientist and spatial analyst should have on their bookshelf. Like most Handbook type publications it provides depth and breadth on the basics of the industrial clustering concept. However, unlike most of these type of collections, it goes beyond the foundation material to identify and speculate on questions that are emerging on the research frontiers such as at the intersection of cluster theory and agglomeration processes, knowledge spillovers and technology transfer not to mention the obvious link to economic development theory, policy and practice. Roger R. Stough, George Mason University, US This eclectic volume presents a host of methods to describe tendencies for the joint location of economic agents in space. And it illustrates useful applications of these concepts in diverse fields financial services, culture, tourism, and industry, to name just a few. John M. Quigley, University of California, US Clusters have increasingly dominated local and regional development policies in recent decades and the growing intellectual and political interest for clusters and clustering is the prime motivation for this Handbook. Charlie Karlsson unites leading experts to present a thorough overview of economic cluster research. Topics explored include agglomeration and cluster theory, methods for analysing clusters, clustering in different spatial contexts and clustering in service industries. Encompassing the developed economies of Europe and North America, the Handbook provides a basis for improving cluster policy formulation, interpretation and analyses. This comprehensive overview of research on economic clusters will be of interest to scholars and PhD students in (regional) economics, economic geography, regional planning and management as well as practitioners and policymakers at the national, regional and local levels involved in cluster formation and cluster management.
Book Synopsis Handbook of Research on Cluster Theory by : Charlie Karlsson
Download or read book Handbook of Research on Cluster Theory written by Charlie Karlsson and published by Edward Elgar Publishing. This book was released on 2010-01-01 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Karlsson has assembled a strong mix of papers that collectively provide a good sense of some of the latest research in the field. Edward Feser, Review of Regional Studies This is a book every regional scientist and spatial analyst should have on their bookshelf. Like most Handbook type publications it provides depth and breadth on the basics of the industrial clustering concept. However, unlike most of these type of collections, it goes beyond the foundation material to identify and speculate on questions that are emerging on the research frontiers such as at the intersection of cluster theory and agglomeration processes, knowledge spillovers and technology transfer not to mention the obvious link to economic development theory, policy and practice. Roger R. Stough, George Mason University, US This eclectic volume presents a host of methods to describe tendencies for the joint location of economic agents in space. And it illustrates useful applications of these concepts in diverse fields financial services, culture, tourism, and industry, to name just a few. John M. Quigley, University of California, US Clusters have increasingly dominated local and regional development policies in recent decades and the growing intellectual and political interest for clusters and clustering is the prime motivation for this Handbook. Charlie Karlsson unites leading experts to present a thorough overview of economic cluster research. Topics explored include agglomeration and cluster theory, methods for analysing clusters, clustering in different spatial contexts and clustering in service industries. Encompassing the developed economies of Europe and North America, the Handbook provides a basis for improving cluster policy formulation, interpretation and analyses. This comprehensive overview of research on economic clusters will be of interest to scholars and PhD students in (regional) economics, economic geography, regional planning and management as well as practitioners and policymakers at the national, regional and local levels involved in cluster formation and cluster management.
The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. 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. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.
Book Synopsis An Introduction to Clustering with R by : Paolo Giordani
Download or read book An Introduction to Clustering with R written by Paolo Giordani and published by Springer Nature. This book was released on 2020-08-27 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. 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. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.
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 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.
The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Book Synopsis Handbook of Pattern Recognition and Computer Vision by : C. H. Chen
Download or read book Handbook of Pattern Recognition and Computer Vision written by C. H. Chen and published by World Scientific. This book was released on 1999 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The very significant advances in computer vision and pattern recognition and their applications in the last few years reflect the strong and growing interest in the field as well as the many opportunities and challenges it offers. The second edition of this handbook represents both the latest progress and updated knowledge in this dynamic field. The applications and technological issues are particularly emphasized in this edition to reflect the wide applicability of the field in many practical problems. To keep the book in a single volume, it is not possible to retain all chapters of the first edition. However, the chapters of both editions are well written for permanent reference.
Although clustering--the classification of objects into meaningful sets--is an important procedure in the social sciences today, cluster analysis as a multivariate statistical procedure is poorly understood by many social scientists. This volume is an introduction to cluster analysis for social scientists and students.
Book Synopsis Cluster Analysis by : Mark S. Aldenderfer
Download or read book Cluster Analysis written by Mark S. Aldenderfer and published by Chronicle Books. This book was released on 1984-11 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although clustering--the classification of objects into meaningful sets--is an important procedure in the social sciences today, cluster analysis as a multivariate statistical procedure is poorly understood by many social scientists. This volume is an introduction to cluster analysis for social scientists and students.
With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many
Book Synopsis Handbook of Statistical Analyses Using Stata by : Brian S. Everitt
Download or read book Handbook of Statistical Analyses Using Stata written by Brian S. Everitt and published by CRC Press. This book was released on 2006-11-15 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: With each new release of Stata, a comprehensive resource is needed to highlight the improvements as well as discuss the fundamentals of the software. Fulfilling this need, AHandbook of Statistical Analyses Using Stata, Fourth Edition has been fully updated to provide an introduction to Stata version 9. This edition covers many
Back in print at a good price. To see the many websites referencing this book, in Google enter "cluster analysis" (in quotes) and Romesburg. Headlines of 5-star reviews on Amazon.com: "A very clear 'how to' book on cluster analysis" (C. Fielitz, Bristol, TN); "An excellent introduction to cluster analysis" (T. W. Powell, Shreveport, LA). A recent (2004) review in Journal of Classification (21:279-283) says: "We should be grateful to the author for his insistence in bringing forth important issues, which have not got yet that level of attention they deserve. I wish this journal could devote more efforts in promoting the scientific inquiry and discussions of methodology of clustering in scientific research [as Cluster Analysis for Researchers does]." To see or search inside the book, go to www.google.com, type in the book's title, and click on it when it comes up (or copy and paste in your browser's window the following URL: http://print.google.com/print?isbn=1411606175 ).
Book Synopsis Cluster Analysis for Researchers by : Charles Romesburg
Download or read book Cluster Analysis for Researchers written by Charles Romesburg and published by Lulu.com. This book was released on 2004 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Back in print at a good price. To see the many websites referencing this book, in Google enter "cluster analysis" (in quotes) and Romesburg. Headlines of 5-star reviews on Amazon.com: "A very clear 'how to' book on cluster analysis" (C. Fielitz, Bristol, TN); "An excellent introduction to cluster analysis" (T. W. Powell, Shreveport, LA). A recent (2004) review in Journal of Classification (21:279-283) says: "We should be grateful to the author for his insistence in bringing forth important issues, which have not got yet that level of attention they deserve. I wish this journal could devote more efforts in promoting the scientific inquiry and discussions of methodology of clustering in scientific research [as Cluster Analysis for Researchers does]." To see or search inside the book, go to www.google.com, type in the book's title, and click on it when it comes up (or copy and paste in your browser's window the following URL: http://print.google.com/print?isbn=1411606175 ).
