This code implements methods for automatic cluster reinforcement and hierarchical cluster visualization of sparsely-matched SOMs, described in:
N. Manukyan, M.J. Eppstein, D.M. Rizzo,"Data-driven cluster reinforcement and visualization in sparsely-matched self-organizing maps," Neural Networks and learning Systems, IEEE Transactions on, vol23, no 5, pp 846-852,may 2012 (see abstract below).
The primary functions are:
CR.m (Cluster Reinforcement Phase for SOM)
B_matrix.m (Create Boundary Distance Matrix)
Plot_B.m (Display B-matrix as a heat map)
PlotBLines.m (Display B-values as grid lines on top of component planes)
The driver function demoCR.m illustrates how to use these functions on an already trained SOM using Kohonen's animal data.
We also provide SOM code (SOM.m) for users convenience.
ABSTRACT: The Cluster Reinforcement phase advances cluster separation in a self-organizing map (SOM) by strengthening cluster boundaries in a data-driven manner. SOM is a self-organized projection of high dimensional data onto a typically two dimensional (2D) feature map, wherein vector similarity is implicitly translated into topological closeness in the 2D projection. The CR phase amplifies within-cluster similarity in an unsupervised, data-driven manner. Discontinuities in the resulting map correspond to between-cluster distances and are stored in a boundary (B) matrix. CR phase enables a new hierarchical visualization of cluster boundaries displayed directly on feature maps, which requires no further clustering beyond what was implicitly accomplished during self-organization in SOM training.
Added full reference to paper.
Minor fix in SOM code.
Fixed toroidal training for SOM.
added a file
SOM (self-organizing map) code added.
Added new files