Graphs as Structural Models: The Application of Graphs and Multigraphs in Cluster Analysis
The advent of the high-speed computer with its enormous storage capabilities enabled statisticians as well as researchers from the different topics of life sciences to apply mul tivariate statistical procedures to large data sets to explore their structures. More and more, methods of graphical repr...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Wiesbaden
Vieweg+Teubner Verlag
1988
|
| Schriftenreihe: | Advances in System Analysis
|
| Schlagworte: | |
| Online-Zugang: | BTU01 Volltext |
| Zusammenfassung: | The advent of the high-speed computer with its enormous storage capabilities enabled statisticians as well as researchers from the different topics of life sciences to apply mul tivariate statistical procedures to large data sets to explore their structures. More and more, methods of graphical representation and data analysis are used for investigations. These methods belong to a topic of growing popUlarity, known as "exploratory data analysis" or EDA. In many applications, there is reason to believe that a set of objects can be clus tered into subgroups that differ in meaningful ways. Extensive data sets, for example, are stored in clinical cancer registers. In large data sets like these, nobody would ex pect the objects to be homogeneous. The most commonly used terms for the class of procedures that seek to separate the component data into groups are "cluster analysis" or "numerical taxonomy". The origins of cluster analysis can be found in biology and anthropology at the beginning of the century. The first systematic investigations in cluster analysis are those of K. Pearson in 1894. The search for classifications or ty pologies of objects or persons, however, is indigenous not only to biology but to a wide variety of disciplines. Thus, in recent years, a growing interest in classification and related areas has taken place. Today, we see applications of cluster analysis not only to. biology but also to such diverse areas as psychology, regional analysis, marketing research, chemistry, archaeology and medicine |
| Beschreibung: | 1 Online-Ressource (X, 214 p) |
| ISBN: | 9783322963109 |
| DOI: | 10.1007/978-3-322-96310-9 |
Internformat
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Datensatz im Suchindex
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| author | Godehardt, Erhard |
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| author_role | aut |
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| author_variant | e g eg |
| building | Verbundindex |
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| collection | ZDB-2-ENG |
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| dewey-full | 511.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 511 - General principles of mathematics |
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| dewey-search | 511.5 |
| dewey-sort | 3511.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| doi_str_mv | 10.1007/978-3-322-96310-9 |
| format | Electronic eBook |
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| series2 | Advances in System Analysis |
| spelling | Godehardt, Erhard Verfasser aut Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis by Erhard Godehardt Wiesbaden Vieweg+Teubner Verlag 1988 1 Online-Ressource (X, 214 p) txt rdacontent c rdamedia cr rdacarrier Advances in System Analysis The advent of the high-speed computer with its enormous storage capabilities enabled statisticians as well as researchers from the different topics of life sciences to apply mul tivariate statistical procedures to large data sets to explore their structures. More and more, methods of graphical representation and data analysis are used for investigations. These methods belong to a topic of growing popUlarity, known as "exploratory data analysis" or EDA. In many applications, there is reason to believe that a set of objects can be clus tered into subgroups that differ in meaningful ways. Extensive data sets, for example, are stored in clinical cancer registers. In large data sets like these, nobody would ex pect the objects to be homogeneous. The most commonly used terms for the class of procedures that seek to separate the component data into groups are "cluster analysis" or "numerical taxonomy". The origins of cluster analysis can be found in biology and anthropology at the beginning of the century. The first systematic investigations in cluster analysis are those of K. Pearson in 1894. The search for classifications or ty pologies of objects or persons, however, is indigenous not only to biology but to a wide variety of disciplines. Thus, in recent years, a growing interest in classification and related areas has taken place. Today, we see applications of cluster analysis not only to. biology but also to such diverse areas as psychology, regional analysis, marketing research, chemistry, archaeology and medicine Mathematics Graph Theory Models and Principles Mathematics, general Computers Graph theory Cluster-Analyse (DE-588)4070044-6 gnd rswk-swf Graph (DE-588)4021842-9 gnd rswk-swf Graphentheorie (DE-588)4113782-6 gnd rswk-swf Cluster-Analyse (DE-588)4070044-6 s Graphentheorie (DE-588)4113782-6 s 1\p DE-604 Graph (DE-588)4021842-9 s 2\p DE-604 Erscheint auch als Druck-Ausgabe 9783528063122 https://doi.org/10.1007/978-3-322-96310-9 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Godehardt, Erhard Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis Mathematics Graph Theory Models and Principles Mathematics, general Computers Graph theory Cluster-Analyse (DE-588)4070044-6 gnd Graph (DE-588)4021842-9 gnd Graphentheorie (DE-588)4113782-6 gnd |
| subject_GND | (DE-588)4070044-6 (DE-588)4021842-9 (DE-588)4113782-6 |
| title | Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis |
| title_auth | Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis |
| title_exact_search | Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis |
| title_full | Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis by Erhard Godehardt |
| title_fullStr | Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis by Erhard Godehardt |
| title_full_unstemmed | Graphs as Structural Models The Application of Graphs and Multigraphs in Cluster Analysis by Erhard Godehardt |
| title_short | Graphs as Structural Models |
| title_sort | graphs as structural models the application of graphs and multigraphs in cluster analysis |
| title_sub | The Application of Graphs and Multigraphs in Cluster Analysis |
| topic | Mathematics Graph Theory Models and Principles Mathematics, general Computers Graph theory Cluster-Analyse (DE-588)4070044-6 gnd Graph (DE-588)4021842-9 gnd Graphentheorie (DE-588)4113782-6 gnd |
| topic_facet | Mathematics Graph Theory Models and Principles Mathematics, general Computers Graph theory Cluster-Analyse Graph Graphentheorie |
| url | https://doi.org/10.1007/978-3-322-96310-9 |
| work_keys_str_mv | AT godehardterhard graphsasstructuralmodelstheapplicationofgraphsandmultigraphsinclusteranalysis |