<p>Cluster coefficients for homogeneity (cluster compactness) and separation for selected ecosystems and -subsystems (including all samples).</p
<p>Average clustering coefficient for varying <i>N</i> and <i>MTE</i> = 10×<i>N</i>.</p
<p>Numbers in the last three columns represent the most characteristic value in terms of phenotypic ...
<p>CLUSTER analysis for community composition data, based on Bray Curtis Similarity indices.</p
<p>Recategorized combined habitat factor categories based on divergences in community size structure...
Characteristics of the 2 clusters obtained by a hierarchical cluster analysis.</p
Agglomeration coefficients and coefficient change for different cluster solutions.</p
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
<p>Mean and standard deviation (error bars) of the distance of the farthest individual from its clus...
<p>Mean clustering coefficient for different values of <i>σ</i> (standard deviation of the dispersal...
Clustering seeks to group or to lump together objects or variables that share some observed qualitie...
<p>Clustering coefficient (A) and degree assortativity (B) values generated by the CMext and SpecNet...
<p>Clustering analysis results, indicating the number, configuration and distinctiveness (mixing pro...
<p>Columns from left to right: (1) name of the dataset used; (2) number of morphospecies that each d...
(A) Clustering averages across all samples, (B) Cluster 2 molecules concentration details across all...
Finding compact and well-separated clusters in data sets is a challenging task. Most clustering algo...
<p>Average clustering coefficient for varying <i>N</i> and <i>MTE</i> = 10×<i>N</i>.</p
<p>Numbers in the last three columns represent the most characteristic value in terms of phenotypic ...
<p>CLUSTER analysis for community composition data, based on Bray Curtis Similarity indices.</p
<p>Recategorized combined habitat factor categories based on divergences in community size structure...
Characteristics of the 2 clusters obtained by a hierarchical cluster analysis.</p
Agglomeration coefficients and coefficient change for different cluster solutions.</p
Cluster Analysis aims at finding subsets (clusters) of a given set of entities, which are homogeneou...
<p>Mean and standard deviation (error bars) of the distance of the farthest individual from its clus...
<p>Mean clustering coefficient for different values of <i>σ</i> (standard deviation of the dispersal...
Clustering seeks to group or to lump together objects or variables that share some observed qualitie...
<p>Clustering coefficient (A) and degree assortativity (B) values generated by the CMext and SpecNet...
<p>Clustering analysis results, indicating the number, configuration and distinctiveness (mixing pro...
<p>Columns from left to right: (1) name of the dataset used; (2) number of morphospecies that each d...
(A) Clustering averages across all samples, (B) Cluster 2 molecules concentration details across all...
Finding compact and well-separated clusters in data sets is a challenging task. Most clustering algo...
<p>Average clustering coefficient for varying <i>N</i> and <i>MTE</i> = 10×<i>N</i>.</p
<p>Numbers in the last three columns represent the most characteristic value in terms of phenotypic ...
<p>CLUSTER analysis for community composition data, based on Bray Curtis Similarity indices.</p
DOI
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