Mathematical Classification and Clustering:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1996
|
| Schriftenreihe: | Nonconvex Optimization and Its Applications
11 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor |
| Beschreibung: | 1 Online-Ressource (448p) |
| ISBN: | 9781461304579 9781461380573 |
| ISSN: | 1571-568X |
| DOI: | 10.1007/978-1-4613-0457-9 |
Internformat
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| 500 | |a I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor | ||
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Datensatz im Suchindex
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| author | Mirkin, Boris |
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| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-1-4613-0457-9 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-07-10T01:21:07Z |
| institution | BVB |
| isbn | 9781461304579 9781461380573 |
| issn | 1571-568X |
| language | English |
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| spelling | Mirkin, Boris Verfasser aut Mathematical Classification and Clustering by Boris Mirkin Boston, MA Springer US 1996 1 Online-Ressource (448p) txt rdacontent c rdamedia cr rdacarrier Nonconvex Optimization and Its Applications 11 1571-568X I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor Statistics Artificial intelligence Mathematical optimization Statistics, general Artificial Intelligence (incl. Robotics) Operations Research/Decision Theory Optimization Künstliche Intelligenz Statistik Cluster-Analyse (DE-588)4070044-6 gnd rswk-swf Klassifikationstheorie (DE-588)4164034-2 gnd rswk-swf Cluster-Analyse (DE-588)4070044-6 s Klassifikationstheorie (DE-588)4164034-2 s 1\p DE-604 https://doi.org/10.1007/978-1-4613-0457-9 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Mirkin, Boris Mathematical Classification and Clustering Statistics Artificial intelligence Mathematical optimization Statistics, general Artificial Intelligence (incl. Robotics) Operations Research/Decision Theory Optimization Künstliche Intelligenz Statistik Cluster-Analyse (DE-588)4070044-6 gnd Klassifikationstheorie (DE-588)4164034-2 gnd |
| subject_GND | (DE-588)4070044-6 (DE-588)4164034-2 |
| title | Mathematical Classification and Clustering |
| title_auth | Mathematical Classification and Clustering |
| title_exact_search | Mathematical Classification and Clustering |
| title_full | Mathematical Classification and Clustering by Boris Mirkin |
| title_fullStr | Mathematical Classification and Clustering by Boris Mirkin |
| title_full_unstemmed | Mathematical Classification and Clustering by Boris Mirkin |
| title_short | Mathematical Classification and Clustering |
| title_sort | mathematical classification and clustering |
| topic | Statistics Artificial intelligence Mathematical optimization Statistics, general Artificial Intelligence (incl. Robotics) Operations Research/Decision Theory Optimization Künstliche Intelligenz Statistik Cluster-Analyse (DE-588)4070044-6 gnd Klassifikationstheorie (DE-588)4164034-2 gnd |
| topic_facet | Statistics Artificial intelligence Mathematical optimization Statistics, general Artificial Intelligence (incl. Robotics) Operations Research/Decision Theory Optimization Künstliche Intelligenz Statistik Cluster-Analyse Klassifikationstheorie |
| url | https://doi.org/10.1007/978-1-4613-0457-9 |
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