We propose a visual cluster analysis system that allows to validate the output of the SOM algorithm by comparison with alternative clustering methods.
ABSTRACT. The Self-Organizing Map (SOM) algorithm [4] is a popular and widely used cluster algorithm. Its constraint to organize clusters.
We propose a visual cluster analysis system that allows to validate the output of the SOM algorithm by comparison with alternative clustering methods.
Cluster Correspondence Views for Enhanced Analysis of SOM Displays ; English · 2010 IEEE Symposium on Visual Analytics Science and Technology · Piscataway, NJ.
ABSTRACT. The Self-Organizing Map (SOM) algorithm [4] is a popular and widely used cluster algorithm. Its constraint to organize clusters.
Cluster correspondence views for enhanced analysis of SOM displays
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Cluster correspondence views for enhanced analysis of SOM displays. J. Bernard, T. von Landesberger, S. Bremm, T. Schreck.
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Cluster correspondence views for enhanced analysis of SOM displays. Jurgen Bernard 1. ,. Tatiana Von Landesberger 2. ,. Sebastian Bremm 1. ,. Tobias Schreck 1.
We are specifically interested in enhancing the cluster correspondence views by additional supportive cluster algorithms. Finally, more deep evaluation of ...
We define, measure, and visualize the notion of SOM cluster quality along a hierarchy of cluster abstractions. The quality abstractions range from simple scalar ...
Nov 18, 2020 · We present GigaSOM.jl, a fast and scalable implementation of clustering and dimensionality reduction for flow and mass cytometry data.