A new procedure to optimize the selection of groups in a classification tree: Applications for ecological data

Agglomerative cluster analyses encompass many techniques, which have been widely used in various fields of science. In biology, and specifically ecology, datasets are generally highly variable and may contain outliers, which increase the difficulty to identify the number of clusters. Here we present...

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Veröffentlicht in:	Ecological modelling Jg. 220; H. 4; S. 451 - 461
Hauptverfasser:	Guidi, Lionel, Ibanez, Frédéric, Calcagno, Vincent, Beaugrand, Grégory
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 24.02.2009 Elsevier
Schlagworte:	Animal, plant and microbial ecology Biological and medical sciences Classification Clustering Copepoda Dendrogram Fundamental and applied biological sciences. Psychology General aspects. Techniques Life Sciences Methods and techniques (sampling, tagging, trapping, modelling...) Outliers Stopping rule Outliers Stopping rule Clustering Dendrogram Classification Group selection Ecology Models classification stopping rule outliers
ISSN:	0304-3800, 1872-7026
Online-Zugang:	Volltext
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