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Handbook of cluster analysis / edited by Christian Hennig, University College London, UK, Marina Meila, University of Washington, Seattle, USA, Fionn Murtagh, University of Derby, UK, Goldsmiths, University of London, UK, Roberto Rocci, University of Rome Tor Vergata, Italy.

Contributor(s): Hennig, Christian M [editor.] | Meilă, Marina, 1962- [editor] | Murtagh, Fionn [editor.] | Rocci, Roberto [editor.].
Series: Chapman & Hall/CRC handbooks of modern statistical methods ; 9.Boca Raton, Florida, USA : CRC Press, Taylor & Francis Group, ©2016Description: xx, 753 pages : illustrations ; 26 cm.Content type: text. ISBN: 9781466551886 (alk. paper); 1466551887 (alk. paper).Subject(s): Cluster analysis | Spatial analysis (Statistics)DDC classification: 519.53/H19 Other classification: CAS
Contents:
Cluster Analysis: An Overview Christian M. Hennig and Marina MeilaA Brief History of Cluster Analysis Fionn MurtaghOptimization MethodsQuadratic Error and k-Means Boris MirkinK-Medoids and Other Criteria for Crisp Clustering Douglas SteinleyFoundations for Center-Based Clustering: Worst-Case Approximations and Modern Developments Pranjal Awasthi and Maria Florina BalcanDissimilarity-Based MethodsHierarchical Clustering Pedro Contreras and Fionn MurtaghSpectral Clustering Marina MeilaMethods Based on Probability ModelsMixture Models for Standard p-Dimensional Euclidean Data Geoffrey J. McLachlan and Suren I. RathnayakeLatent Class Models for Categorical Data G. Celeux and Gerard GovaertDirichlet Process Mixtures and Nonparametric Bayesian Approaches to Clustering Vinayak RaoFinite Mixtures of Structured Models Marco Alfo and Sara VivianiTime-Series Clustering Jorge Caiado, Elizabeth Ann Maharaj, and Pierpaolo D'UrsoClustering Functional Data David B. Hitchcock and Mark C. GreenwoodMethods Based on Spatial Processes Lisa Handl, Christian Hirsch, and Volker SchmidtSignificance Testing in Clustering Hanwen Huang, Yufeng Liu, David Neil Hayes, Andrew Nobel, J.S. Marron, and Christian M. HennigModel-Based Clustering for Network Data Thomas Brendan MurphyMethods Based on Density Modes and Level SetsA Formulation in Modal Clustering Based on Upper Level Sets Adelchi AzzaliniClustering Methods Based on Kernel Density Estimators: Mean-Shift Algorithms Miguel A. Carreira-PerpinanNature-Inspired Clustering Julia Handl and Joshua KnowlesSpecific Cluster and Data FormatsSemi-Supervised Clustering Anil Jain, Rong Jin, and Radha ChittaClustering of Symbolic Data Paula BritoA Survey of Consensus Clustering Joydeep Ghosh and Ayan AcharyaTwo-Mode Partitioning and Multipartitioning Maurizio VichiFuzzy Clustering Pierpaolo D'UrsoRough Set Clustering Ivo Duntsch and Gunther GedigaCluster Validation and Further General IssuesMethod-Independent Indices for Cluster Validation and Estimating the Number of Clusters Maria Halkidi, Michalis Vazirgiannis, and Christian M. HennigCriteria for Comparing Clusterings Marina MeilaResampling Methods for Exploring Cluster Stability Friedrich LeischRobustness and Outliers L.A. Garcia-Escudero, A. Gordaliza, C. Matran, A. Mayo-Iscar, and Christian M. HennigVisual Clustering for Data Analysis and Graphical User Interfaces Sebastien Dejean and Josiane MotheClustering Strategy and Method Selection Christian M. Hennig
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"A Chapman & Hall book."

Includes bibliographical references and index.

Cluster Analysis: An Overview Christian M. Hennig and Marina MeilaA Brief History of Cluster Analysis Fionn MurtaghOptimization MethodsQuadratic Error and k-Means Boris MirkinK-Medoids and Other Criteria for Crisp Clustering Douglas SteinleyFoundations for Center-Based Clustering: Worst-Case Approximations and Modern Developments Pranjal Awasthi and Maria Florina BalcanDissimilarity-Based MethodsHierarchical Clustering Pedro Contreras and Fionn MurtaghSpectral Clustering Marina MeilaMethods Based on Probability ModelsMixture Models for Standard p-Dimensional Euclidean Data Geoffrey J. McLachlan and Suren I. RathnayakeLatent Class Models for Categorical Data G. Celeux and Gerard GovaertDirichlet Process Mixtures and Nonparametric Bayesian Approaches to Clustering Vinayak RaoFinite Mixtures of Structured Models Marco Alfo and Sara VivianiTime-Series Clustering Jorge Caiado, Elizabeth Ann Maharaj, and Pierpaolo D'UrsoClustering Functional Data David B. Hitchcock and Mark C. GreenwoodMethods Based on Spatial Processes Lisa Handl, Christian Hirsch, and Volker SchmidtSignificance Testing in Clustering Hanwen Huang, Yufeng Liu, David Neil Hayes, Andrew Nobel, J.S. Marron, and Christian M. HennigModel-Based Clustering for Network Data Thomas Brendan MurphyMethods Based on Density Modes and Level SetsA Formulation in Modal Clustering Based on Upper Level Sets Adelchi AzzaliniClustering Methods Based on Kernel Density Estimators: Mean-Shift Algorithms Miguel A. Carreira-PerpinanNature-Inspired Clustering Julia Handl and Joshua KnowlesSpecific Cluster and Data FormatsSemi-Supervised Clustering Anil Jain, Rong Jin, and Radha ChittaClustering of Symbolic Data Paula BritoA Survey of Consensus Clustering Joydeep Ghosh and Ayan AcharyaTwo-Mode Partitioning and Multipartitioning Maurizio VichiFuzzy Clustering Pierpaolo D'UrsoRough Set Clustering Ivo Duntsch and Gunther GedigaCluster Validation and Further General IssuesMethod-Independent Indices for Cluster Validation and Estimating the Number of Clusters Maria Halkidi, Michalis Vazirgiannis, and Christian M. HennigCriteria for Comparing Clusterings Marina MeilaResampling Methods for Exploring Cluster Stability Friedrich LeischRobustness and Outliers L.A. Garcia-Escudero, A. Gordaliza, C. Matran, A. Mayo-Iscar, and Christian M. HennigVisual Clustering for Data Analysis and Graphical User Interfaces Sebastien Dejean and Josiane MotheClustering Strategy and Method Selection Christian M. Hennig

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