The SPAWNN toolkit is an innovative toolkit for spatial analysis with self-organizing neural networks which is particularily useful for spatial analysis, visualization and geographical data mining.

To run the toolkit, simply download and execute (double-click) the jar-file.

Please cite:
- Hagenauer, J., & Helbich, M. (2016). SPAWNN: A Toolkit for SPatial Analysis With Self-Organizing Neural Networks. Transactions in GIS, 20(5), 755-775.

Other related publications:
- Hagenauer, J. (2016). Weighted merge context for clustering and quantizing spatial data with self-organizing neural networks. Journal of Geographical Systems, 18(1), 1-15.
- Hagenauer, J., & Helbich, M. (2013). Contextual neural gas for spatial clustering and analysis. International Journal of Geographical Information Science, 27(2), 251-266.

Features

  • Implements Self-Organizing Map and Neural Gas algorithms
  • Supports different approaches for considering spatial dependence
  • Provides linkage between networks and geographical data
  • Implements powerful clustering algorithms for structuring the networks

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Categories

Machine Learning, GIS

License

GNU General Public License version 3.0 (GPLv3)

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Additional Project Details

Registered

2015-08-02