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.
"synopsis" may belong to another edition of this title.
Christian Hennig is a senior lecturer in the Department of Statistical Science at University College London. Dr. Hennig is currently secretary of the International Federation of Classification Societies and associate editor of Statistics and Computing, Computational Statistics and Data Analysis, Advances in Data Analysis and Classification, and Statistical Methods and Applications. His main research interests are cluster analysis, philosophy of statistics, robust statistics, multivariate analysis, data visualization, and model selection.
Marina Meila is a professor of statistics at the University of Washington. She earned a PhD in computer science and electrical engineering from the Massachusetts Institute of Technology. Her long-term interest is in machine learning and reasoning in uncertainty and how these can be performed efficiently on large, complex data sets.
Fionn Murtagh is a professor of data science at University of Derby and Goldsmiths University of London. Dr. Murtagh is a fellow of the International Association for Pattern Recognition, a fellow of the British Computer Society, an elected member of the Royal Irish Academy and Academia Europaea, a member of the editorial boards of many journals, and editor-in-chief of the Computer Journal. His research interests encompass data science and big data analytics.
Roberto Rocci is a professor of statistics in the Department of Economics and Finance at the University of Rome Tor Vergata. Dr. Rocci is associate editor of the Statistical Methods and Applications Journal and board member of the SIS-CLassification and Data Analysis Group (SIS-CLADAG). His research interests include cluster analysis, mixture models, and latent variable models.
"About this title" may belong to another edition of this title.
US$ 2.64 shipping within U.S.A.
Destination, rates & speedsSeller: Basi6 International, Irving, TX, U.S.A.
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEJUNE24-391066
Quantity: 1 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 41473705-n
Quantity: 10 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. pp. 773. Seller Inventory # 385859641
Quantity: 3 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 41473705
Quantity: 10 available
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. pp. 773. Seller Inventory # 26378044390
Quantity: 4 available
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 773 pages. 10.00x7.01x1.57 inches. In Stock. Seller Inventory # __0367570408
Quantity: 1 available
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 753 pp. Englisch. Seller Inventory # 9780367570408
Quantity: 2 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9780367570408_new
Quantity: Over 20 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 41473705-n
Quantity: 10 available
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New. PRINT ON DEMAND pp. 773. Seller Inventory # 18378044396
Quantity: 4 available