{ "info": { "author": "Felix M. Riese", "author_email": "github@felixriese.de", "bugtrack_url": null, "classifiers": [ "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Education", "Intended Audience :: Information Technology", "Intended Audience :: Science/Research", "License :: OSI Approved", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering" ], "description": ".. image:: https://badge.fury.io/py/susi.svg\n :target: https://pypi.org/project/susi/\n :alt: PyPi - Code Version\n\n.. image:: https://img.shields.io/pypi/pyversions/susi.svg\n :target: https://pypi.org/project/susi/\n :alt: PyPI - Python Version\n\n.. image:: https://img.shields.io/pypi/l/susi.svg\n :target: https://github.com/felixriese/susi/blob/master/LICENSE\n :alt: PyPI - License\n\n.. image:: https://travis-ci.org/felixriese/susi.svg?branch=master\n :target: https://travis-ci.org/felixriese/susi\n :alt: Travis.CI Status\n\n.. image:: https://readthedocs.org/projects/susi/badge/?version=latest\n :target: https://susi.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. image:: https://codecov.io/gh/felixriese/susi/branch/master/graph/badge.svg\n :target: https://codecov.io/gh/felixriese/susi\n :alt: Codecov\n\n.. image:: https://api.codacy.com/project/badge/Grade/d304689a7364437db1ef998cf7765f5a\n\t:target: https://app.codacy.com/app/felixriese/susi\n\t:alt: Codacy Badge\n\n|\n\nSUSI: SUpervised Self-organIzing maps in Python\n===============================================\n\nPython package for unsupervised and supervised self-organizing maps (SOM)\n\nDescription\n-----------\n\nWe present the SUSI package for Python.\nIt includes a fully functional SOM for unsupervised and supervised tasks.\nThe class structure is set up as follows:\n\n- SOMClustering: Unsupervised SOM for clustering\n\n - SOMEstimator: Base class for supervised SOMs\n\n - SOMRegressor: Regression SOM\n - SOMClassifier: Classification SOM\n\n:License:\n `3-Clause BSD license `_\n\n:Author:\n `Felix M. Riese `_\n\n:Citation:\n see `Citation`_ and in the `bibtex `_ file\n\n:Documentation:\n `Documentation `_\n\n:Installation:\n `Installation guidelines `_\n\n:Paper:\n `arXiv:1903.11114 `_\n\n\nInstallation\n------------\n\n.. code:: bash\n\n pip install susi\n\nMore information can be found in the `installation guidelines `_.\n\nExamples\n--------\n\nA collection of code examples can be found in `the documentation `_.\nCode examples as Jupyter Notebooks can be found here:\n\n* `examples/SOMClustering `_\n* `examples/SOMRegressor_Hyperspectral `_\n* `examples/SOMRegressor_semisupervised `_\n* `examples/SOMClassifier `_\n* `examples/SOMClassifier_Salinas `_\n* `examples/SOMClassifier_semisupervised `_\n\nCitation\n--------\n\nThe bibtex file including both references is available `here `_.\n\n**Paper:**\n\nFelix M. Riese and S. Keller, \"SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python\", `arXiv:1903.11114 `_, 2019. Submitted to an ISPRS conference.\n\n.. code:: bibtex\n\n @article{riesekeller2019susi,\n author = {Riese, Felix~M. and Keller, Sina},\n title = {SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python},\n year = {2019},\n archivePrefix = {arXiv},\n eprint = {1903.11114},\n primaryClass = {cs.LG},\n url = {https://arxiv.org/abs/1903.11114}\n }\n\n**Code:**\n\nFelix M. Riese, \"SUSI: SUpervised Self-organIzing maps in Python\", `10.5281/zenodo.2609130 `_, 2019.\n\n.. image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2609130.svg\n :target: https://doi.org/10.5281/zenodo.2609130\n\n.. code:: bibtex\n\n @misc{riese2019susicode,\n author = {Riese, Felix~M.},\n title = {{SUSI: SUpervised Self-organIzing maps in Python}},\n year = {2019},\n DOI = {10.5281/zenodo.2609130},\n publisher = {Zenodo},\n howpublished = {\\href{https://doi.org/10.5281/zenodo.2609130}{doi.org/10.5281/zenodo.2609130}}\n }\n\n\nChange Log\n==========\n\n[1.0.6] - 2019-09-11\n------------------------\n- [ADDED] Semi-supervised abilities for classifier and regressor\n- [ADDED] Example notebooks for semi-supervised applications\n- [ADDED] Tests for example notebooks\n- [FIXED] Code looks better in documentation with sphinx.ext.napoleon\n- [CHANGED] Requirements for the SUSI package\n- [REMOVED] Support for Python 3.4\n\n[1.0.5] - 2019-04-23\n------------------------\n- [ADDED] PCA initialization of the SOM weights with 2 principal components\n- [ADDED] Variable variance\n- [CHANGED] Moved installation guidelines and examples to documentation\n\n[1.0.4] - 2019-04-21\n------------------------\n- [ADDED] Batch algorithm for unsupervised and supervised SOM\n- [ADDED] Calculation of the unified distance matrix (u-matrix)\n- [FIXED] Added estimator_check of scikit-learn and fixed recognized issues\n\n[1.0.3] - 2019-04-09\n------------------------\n- [ADDED] Link to arXiv paper\n- [ADDED] Mexican-hat neighborhood distance weight\n- [ADDED] Possibility for different initialization modes\n- [CHANGED] Simplified initialization of estimators\n- [FIXED] URLs and styles in documentation\n- [FIXED] Colormap in Salinas example\n\n[1.0.2] - 2019-03-27\n------------------------\n- [CHANGED] Moved decreasing_rate() out of SOM classes\n- [FIXED] Removed duplicate constructor for SOMRegressor, fixed fit() params\n- [ADDED] Codecov, Codacy\n\n[1.0.1] - 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