Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)

We present the SuSi package for Python. It includes a fully functional SOM for unsupervised, supervised and semi-supervised tasks:

• SOMClustering: Unsupervised SOM for clustering
• SOMRegressor: (Semi-)Supervised Regression SOM
• SOMClassifier: (Semi-)Supervised Classification SOM

License

3-Clause BSD license

Author

Felix M. Riese

Citation

see Citation and in the bibtex file

Documentation

Documentation

Installation

Installation guidelines

Paper

F. M. Riese, S. Keller and S. Hinz in Remote Sensing, 2020

pip3 install susi

conda install -c conda-forge susi

More information can be found in the installation guidelines.

A collection of code examples can be found in the documentation. Code examples as Jupyter Notebooks can be found here:

• examples/SOMClustering
• examples/SOMRegressor
• examples/SOMRegressor_semisupervised
• examples/SOMRegressor_multioutput
• examples/SOMClassifier
• examples/SOMClassifier_semisupervised

• How should I set the initial hyperparameters of a SOM? For more details on the hyperparameters, see in documentation/hyperparameters.
• How can I optimize the hyperparameters? The SuSi hyperparameters can be optimized, for example, with scikit-learn.model_selection.GridSearchCV, since the SuSi package is developed according to several scikit-learn guidelines.

The bibtex file including both references is available in bibliography.bib.

Paper:

F. M. Riese, S. Keller and S. Hinz, "Supervised and Semi-Supervised Self-Organizing Maps for Regression and Classification Focusing on Hyperspectral Data", Remote Sensing, vol. 12, no. 1, 2020. DOI:10.3390/rs12010007

@article{riese2020supervised,
    author = {Riese, Felix~M. and Keller, Sina and Hinz, Stefan},
    title = {{Supervised and Semi-Supervised Self-Organizing Maps for
              Regression and Classification Focusing on Hyperspectral Data}},
    journal = {Remote Sensing},
    year = {2020},
    volume = {12},
    number = {1},
    article-number = {7},
    URL = {https://www.mdpi.com/2072-4292/12/1/7},
    ISSN = {2072-4292},
    DOI = {10.3390/rs12010007}
}

Code:

Felix M. Riese, "SuSi: SUpervised Self-organIzing maps in Python", Zenodo, 2019. DOI:10.5281/zenodo.2609130

@misc{riese2019susicode,
    author = {Riese, Felix~M.},
    title = {{SuSi: Supervised Self-Organizing Maps in Python}},
    year = {2019},
    DOI = {10.5281/zenodo.2609130},
    publisher = {Zenodo},
    howpublished = {\href{https://doi.org/10.5281/zenodo.2609130}{doi.org/10.5281/zenodo.2609130}}
}

This project is published under the 3-Clause BSD license.