https://github.com/felixriese/susi
SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)
https://github.com/felixriese/susi
data-science machine-learning opensource pypi-package python self-organizing-map semi-supervised-learning som sphinx-doc supervised-learning unsupervised-learning
Last synced: about 1 month ago
JSON representation
SuSi: Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)
- Host: GitHub
- URL: https://github.com/felixriese/susi
- Owner: felixriese
- License: bsd-3-clause
- Created: 2019-03-26T15:25:38.000Z (about 7 years ago)
- Default Branch: main
- Last Pushed: 2025-01-26T12:14:55.000Z (about 1 year ago)
- Last Synced: 2026-01-26T10:34:28.382Z (2 months ago)
- Topics: data-science, machine-learning, opensource, pypi-package, python, self-organizing-map, semi-supervised-learning, som, sphinx-doc, supervised-learning, unsupervised-learning
- Language: Python
- Homepage: https://felixriese.github.io/susi
- Size: 3.71 MB
- Stars: 115
- Watchers: 3
- Forks: 22
- Open Issues: 1
-
Metadata Files:
- Readme: README.rst
- Changelog: CHANGELOG.rst
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
Awesome Lists containing this project
README
.. image:: https://badge.fury.io/py/susi.svg
:target: https://pypi.org/project/susi/
:alt: PyPi - Code Version
.. image:: https://img.shields.io/pypi/pyversions/susi.svg
:target: https://pypi.org/project/susi/
:alt: PyPI - Python Version
.. image:: https://readthedocs.org/projects/susi/badge/?version=latest
:target: https://susi.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. image:: https://codecov.io/gh/felixriese/susi/branch/master/graph/badge.svg
:target: https://codecov.io/gh/felixriese/susi
:alt: Codecov
.. image:: https://api.codacy.com/project/badge/Grade/d304689a7364437db1ef998cf7765f5a
:target: https://app.codacy.com/app/felixriese/susi
:alt: Codacy Badge
.. image:: https://anaconda.org/conda-forge/susi/badges/version.svg
:target: https://anaconda.org/conda-forge/susi
:alt: Conda-forge
|
.. image:: https://raw.githubusercontent.com/felixriese/susi/master/docs/_static/susi_logo_small.png
:target: https://github.com/felixriese/susi
:align: right
:alt: SuSi logo
SuSi: Supervised Self-organizing maps in Python
===============================================
Python package for unsupervised, supervised and semi-supervised self-organizing maps (SOM)
Description
-----------
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 `_
Installation
------------
Pip
~~~
.. code:: bash
pip3 install susi
.. image:: https://static.pepy.tech/personalized-badge/susi?period=total&units=international_system&left_color=black&right_color=blue&left_text=Downloads
:target: https://pepy.tech/project/susi
:alt: PyPi Downloads
Conda
~~~~~
.. code:: bash
conda install -c conda-forge susi
More information can be found in the `installation guidelines `_.
.. image:: https://img.shields.io/conda/dn/conda-forge/susi.svg
:target: https://anaconda.org/conda-forge/susi
:alt: Conda-Forge Downloads
Examples
--------
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 `_
FAQs
-----
- **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.
------------
Citation
--------
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
`_
.. code:: bibtex
@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
`_
.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2609130.svg
:target: https://doi.org/10.5281/zenodo.2609130
.. code:: bibtex
@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}}
}
-------------
License
-------
This project is published under the `3-Clause BSD `_ license.
.. image:: https://img.shields.io/pypi/l/susi.svg
:target: https://github.com/felixriese/susi/blob/main/LICENSE
:alt: PyPI - License