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

Project description

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SuSi: Supervised Self-organizing maps in Python

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


3-Clause BSD license


Felix M. Riese


see Citation and in the bibtex file




Installation guidelines


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



pip3 install susi
PyPi Downloads


conda install -c conda-forge susi

More information can be found in the installation guidelines.

Conda-Forge Downloads


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


  • 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.


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

    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 = {},
    ISSN = {2072-4292},
    DOI = {10.3390/rs12010007}


Felix M. Riese, “SuSi: SUpervised Self-organIzing maps in Python”, Zenodo, 2019. DOI:10.5281/zenodo.2609130
    author = {Riese, Felix~M.},
    title = {{SuSi: Supervised Self-Organizing Maps in Python}},
    year = {2019},
    DOI = {10.5281/zenodo.2609130},
    publisher = {Zenodo},
    howpublished = {\href{}{}}


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

PyPI - License

Change Log

[1.4.0] - 2024-03-29

  • [ADDED] Official support for Python 3.12.

  • [REMOVED] Official support for Python 3.8 (will be deprecated in 10/2024). It might still work, but will not be maintained on this version.

[1.3.0] - 2023-07-08

  • [ADDED] Official support for Python 3.11.

  • [FIXED] Quantization error axis bug.

  • [REMOVED] Official support for Python 3.7 (deprecated in 2023). It might still work, but will not be maintained on this version.

[1.2.2] - 2021-12-11

  • [ADDED] Official support for Python 3.10.

  • [REMOVED] Official support for Python 3.6 (will be deprecated end of 2021 anyways). It might still work, but will not be maintained on this version.

[1.2.1] - 2021-10-19

  • [ADDED] Quantization error get_quantization_error()

[1.2] - 2021-04-04

  • [ADDED] Landing page with vuepress.

  • [ADDED] Conda-forge recipe.

  • [ADDED] Function SOMClassifier.predict_proba()

  • [ADDED] Example notebook for multi-output regression

  • [CHANGED] Code formatting to black.

  • [CHANGED] CI from travis to GitHub actions.

  • [FIXED] Requirements in

[1.1.2] - 2021-02-18

  • [ADDED] Python 3.9 support. Python 3.6 support will be removed soon.

  • [CHANGED] Function names for private use now start with an underscore.

[1.1.1] - 2020-11-18

  • [ADDED] New distance metric “spectralangle”.

  • [ADDED] FAQs.

  • [ADDED] Separate between positional and keyword parameters.

  • [ADDED] Plot script for neighborhood distance weight matrix.

  • [FIXED] Added inherited members to code documentation.

[1.1.0] - 2020-08-31

  • [ADDED] Logo.

  • [ADDED] SOMPlots documentation.

  • [REMOVED] Python 3.5 support. Now, only 3.6-3.8 are supported.

  • [FIXED] Scikit-learn warnings regarding validation of positional arguments.

  • [FIXED] Sphinx documentation warnings.

[1.0.10] - 2020-04-21

  • [ADDED] Support for Python 3.8.x.

  • [ADDED] Test coverage and MultiOutput test.

  • [CHANGED] Function setPlaceholder to _set_placeholder.

  • [FIXED] Documentation links

[1.0.9] - 2020-04-07

  • [ADDED] Documentation of the hyperparameters.

  • [ADDED] Plot scripts.

  • [CHANGED] Structure of the module files.

[1.0.8] - 2020-01-20

  • [FIXED] Replaced scikit-learn sklearn.utils.fixes.parallel_helper, see #12.

[1.0.7] - 2019-11-28

  • [ADDED] Optional tqdm visualization of the SOM training

  • [ADDED] New init_mode_supervised called random_minmax.

  • [CHANGED] Official name of package changes from SUSI to SuSi.

  • [CHANGED] Docstrings for functions are now according to guidelines.

  • [FIXED] Semi-supervised classification handling, sample weights

  • [FIXED] Supervised classification SOM initalization of n_iter_supervised

  • [FIXED] Code refactored according to prospector

  • [FIXED] Resolved bug in get_datapoints_from_node() for unsupervised SOM.

[1.0.6] - 2019-09-11

  • [ADDED] Semi-supervised abilities for classifier and regressor

  • [ADDED] Example notebooks for semi-supervised applications

  • [ADDED] Tests for example notebooks

  • [CHANGED] Requirements for the SuSi package

  • [REMOVED] Support for Python 3.4

  • [FIXED] Code looks better in documentation with sphinx.ext.napoleon

[1.0.5] - 2019-04-23

  • [ADDED] PCA initialization of the SOM weights with 2 principal components

  • [ADDED] Variable variance

  • [CHANGED] Moved installation guidelines and examples to documentation

[1.0.4] - 2019-04-21

  • [ADDED] Batch algorithm for unsupervised and supervised SOM

  • [ADDED] Calculation of the unified distance matrix (u-matrix)

  • [FIXED] Added estimator_check of scikit-learn and fixed recognized issues

[1.0.3] - 2019-04-09

  • [ADDED] Link to arXiv paper

  • [ADDED] Mexican-hat neighborhood distance weight

  • [ADDED] Possibility for different initialization modes

  • [CHANGED] Simplified initialization of estimators

  • [FIXED] URLs and styles in documentation

  • [FIXED] Colormap in Salinas example

[1.0.2] - 2019-03-27

  • [ADDED] Codecov, Codacy

  • [CHANGED] Moved decreasing_rate() out of SOM classes

  • [FIXED] Removed duplicate constructor for SOMRegressor, fixed fit() params

[1.0.1] - 2019-03-26

  • [ADDED] Config file for Travis

  • [ADDED] Requirements for read-the-docs documentation

[1.0.0] - 2019-03-26

  • Initial release

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