SOM IT-vis

Information-Theoretic-Cluster Visualization for Self-Organizing Maps - Companion MATLAB Code:

• If you make use of this SOM IT-vis code please cite the following paper

[1] L. E. Brito da Silva and D. C. Wunsch II, "An Information-Theoretic-Cluster Visualization for Self-Organizing Maps," in IEEE Transactions on Neural Networks and Learning Systems, vol. 29, no. 6, pp. 2595-2613, June 2018.

and refer to this Applied Computational Intelligence Laboratory (ACIL) Github repository as

[2] L. E. Brito da Silva and D. C. Wunsch II, "SOM IT-vis," 2018. [Online].
Available: https://github.com/ACIL-Group/SOM-IT-vis

• The code provided here to generate the SOM IT-vis makes use of the SOMToolbox© for MATLAB:

[3] J. Vesanto, J. Himberg, E. Alhoniemi, and J. Parhankangas, “Self-Organizing Map in Matlab: the SOM Toolbox,” in Proceedings of the Matlab DSP Conference, 1999, pp. 35–40.

which is available at:

http://www.cis.hut.fi/projects/somtoolbox

If using SOMToolbox©, please abide by its copyright rules and reference it appropriately.

• The data sets used in the experiments section of the SOM IT-vis article are available at:

1. UCI machine learning repository:
   http://archive.ics.uci.edu/ml

2. Fundamental Clustering Problems Suite (FCPS):
   https://www.uni-marburg.de/fb12/arbeitsgruppen/datenbionik/data?language_sync=1

3. Clustering basic benchmark:
   http://cs.uef.fi/sipu/datasets

• The "main_example.m" file contains an example of usage of the IT-vis code.