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Exploring Topology Preservation of SOMs with a Graph Based Visualization
(SPRINGER-VERLAG BERLIN, 2008)
The Self-Organizing Map (SOM), which projects a (high-dimensional) data manifold onto a lower-dimensional (usually 2-d) ripid lattice. is it commonly used manifold learning algorithm. However, a postprocessing - that is ...
Automated Clustering of Large Data Sets Based on a Topology Representing Graph
(IEEE, 2009)
A powerful method in analysis of large data sets where there are many natural clusters with varying statistics such as different sizes, shapes, density distribution, is the use of self-organizing maps (SOMs) [1]. However, ...
Exploiting Data Topology in Visualization and Clustering Self-Organizing Maps
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2009)
The self-organizing map (SOM) is a powerful method for visualization, cluster extraction, and data mining. It has been used successfully for data of high dimensionality and complexity where traditional methods may often ...