<p>(a) The population map shows the localization of all 134 body measures in SOM space. The color code assigns the number of measures in each of the 50x50 SOM units, empty units are white. Singleton body measures not included in the meta-measure clusters are highlighted. (b) The same map as in panel (a), where thirteen clusters were detected and assigned with a ‘nick name’ characterizing the measures in the cluster. Their number per cluster is given in parenthesis. (c) Consensus cluster map of the features. Light to deep blue coloring indicates the increasing frequency of pairwise appearance of different features in the same clusters as determined in 100-fold bootstrapped SOM training and clustering. (d) Mean intra-cluster consensus as a fu...
The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constrai...
The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constrai...
<p>The size of the whole brain tractography dataset is reduced by extracting a random sample (1). Fo...
<p>A SOM analysis was performed to group spots with a similar expression pattern, in this way cluste...
<p>Combined consensus clustering and ordination (PCA) of robust species and human subjects. (A) Firs...
Abstract—Data analysis plays an indispensable role for un-derstanding various phenomena. Cluster ana...
Abstract—Data analysis plays an indispensable role for un-derstanding various phenomena. Cluster ana...
<p>Clusters were generated based on Self Organizing Maps (SOM). Group Mean represents mean normalize...
(a) Dendrogram illustrating the results of hierarchical clustering. (b) Silhouette coefficients calc...
Cluster analysis methods are used to classify R unlabeled objects in a P-dimensional space into grou...
<p>(A) The average number of unclassified muscles is shown as a function of the number of clusters. ...
<p>Each individual is represented by a bar showing the individual’s estimated membership to a partic...
Background: High-dimensional biomedical data are frequently clustered to identify subgroup structure...
<p>The x-axis represents district, uc is un-clustered, c is clustered. The columns list on the y-axi...
Abstract –A new clustering algorithm based on emergent SOM is proposed. This algorithm, called U*C, ...
The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constrai...
The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constrai...
<p>The size of the whole brain tractography dataset is reduced by extracting a random sample (1). Fo...
<p>A SOM analysis was performed to group spots with a similar expression pattern, in this way cluste...
<p>Combined consensus clustering and ordination (PCA) of robust species and human subjects. (A) Firs...
Abstract—Data analysis plays an indispensable role for un-derstanding various phenomena. Cluster ana...
Abstract—Data analysis plays an indispensable role for un-derstanding various phenomena. Cluster ana...
<p>Clusters were generated based on Self Organizing Maps (SOM). Group Mean represents mean normalize...
(a) Dendrogram illustrating the results of hierarchical clustering. (b) Silhouette coefficients calc...
Cluster analysis methods are used to classify R unlabeled objects in a P-dimensional space into grou...
<p>(A) The average number of unclassified muscles is shown as a function of the number of clusters. ...
<p>Each individual is represented by a bar showing the individual’s estimated membership to a partic...
Background: High-dimensional biomedical data are frequently clustered to identify subgroup structure...
<p>The x-axis represents district, uc is un-clustered, c is clustered. The columns list on the y-axi...
Abstract –A new clustering algorithm based on emergent SOM is proposed. This algorithm, called U*C, ...
The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constrai...
The Self-Organizing Map (SOM) algorithm is a popular and widely used cluster algorithm. Its constrai...
<p>The size of the whole brain tractography dataset is reduced by extracting a random sample (1). Fo...