Cluster analysis
1. Introduction. How clustering methods are used -- Data sets to be used as examples -- A few cautions about cluster analysis -- 2. Similarity measures. Terminology -- The concept of similarity -- The choice of variables -- Similarity measures -- 3. A review of clustering methods. On the nature of c...
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Beverly Hills, Calif. u.a.
Sage Publ.
1984
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| Schriftenreihe: | Sage University papers / Quantitative applications in the social sciences
44 |
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| Online Zugang: | Publisher description Table of contents |
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Tag hinzufügen | Zusammenfassung: | 1. Introduction. How clustering methods are used -- Data sets to be used as examples -- A few cautions about cluster analysis -- 2. Similarity measures. Terminology -- The concept of similarity -- The choice of variables -- Similarity measures -- 3. A review of clustering methods. On the nature of clusters -- Hierarchical agglomerative methods -- Iterative partitioning methods -- Factor analysis variants -- Other methods -- Determining the number of clusters -- Comparing clustering methods -- 4. Validation techniques. Cophenetic correlation -- Significance tests on variables used to create clusters -- Replication -- Significance tests on external variables -- Monte Carlo procedures -- 5. Cluster analysis software and the literature on clustering -- Collections of subroutines and algorithms -- Statistical packages containing clustering software -- Cluster analysis packages -- Simple cluster analysis programs -- The literature on cluster analysis -- Guide to reporting cluster analysis studies -- Appendix. Example data sets (burial data) -- Notes -- References -- About the authors. This book is designed to be an introduction to cluster analysis for those with no background and for those who need an up-to-date and systematic guide through the maze of concepts, techniques, and algorithms associated with the clustering data. The authors begin by discussing measures of similarity, the input needed to perform any clustering analysis. They note varying theoretical meanings of the concept and discuss the set of empirical measures most commonly used to measure similarity. Various methods for actually identifying the clusters are then described. Finally, they discuss procedures for validating the adequacy of a cluster analysis. At all points, the differing concepts and techniques are compared and evaluated This book is designed to be an introduction to cluster analysis for those with no background and for those who need an up-to-date and systematic guide through the maze of concepts, techniques, and algorithms associated with the clustering data. The authors begin by discussing measures of similarity, the input needed to perform any clustering analysis. They note varying theoretical meanings of the concept and discuss the set of empirical measures most commonly used to measure similarity. Various methods for actually identifying the clusters are then described. Finally, they discuss procedures for validating the adequacy of a cluster analysis. At all points, the differing concepts and techniques are compared and evaluated |
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| Beschreibung: | 86 S. graph. Darst. 22 cm |
| ISBN: | 0803923767 0-8039-2376-7 |