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Hierarchical Clustering

LEESE, MORVEN Howell, David C. ; Everitt, Brian S.

Encyclopedia of Statistics in Behavioral Science, 2005, Vol.2, p.799-805

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Título:
Hierarchical Clustering
Autor: LEESE, MORVEN
Howell, David C. ; Everitt, Brian S.
Assuntos: Cluster analysis ; Distance matrices ; Distance measurement ; Euclidean geometry ; Meta-analysis ; Multilevel analysis ; Multivariate Methods ; Phylogenetic trees ; Statistical methods
É parte de: Encyclopedia of Statistics in Behavioral Science, 2005, Vol.2, p.799-805
Descrição: Hierarchical cluster analysis is contrasted with optimization methods. Different ways of defining similarity or distance between cases and between clusters are given. The hierarchical clustering process is illustrated using single linkage and average linkage on a small data set, and a number of other standard agglomerative and divisive techniques are listed. The role of the dendrogram in illustrating the clustering process and the cophenetic correlation is described, as are methods for the interpretation of clusters and for deciding on the number of clusters. Some potential problems of standard methods are highlighted and model‐based methods are mentioned as an alternative approach.
Editor: Chichester, UK: John Wiley & Sons, Ltd
Idioma: Inglês

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