Metadata-Version: 2.1
Name: susi
Version: 1.0.4
Summary: Python package for unsupervised and supervised self-organizing maps (SOM)
Home-page: https://github.com/felixriese/susi
Author: Felix M. Riese
Author-email: github@felixriese.de
License: BSD-3-Clause
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        |
        
        SUSI: SUpervised Self-organIzing maps in Python
        ===============================================
        
        Python package for unsupervised and supervised self-organizing maps (SOM)
        
        Description
        -----------
        
        We present the SUSI package for Python.
        It includes a fully functional SOM for unsupervised and supervised tasks.
        The class structure is set up as follows:
        
        - SOMClustering: Unsupervised SOM for clustering
        
          - SOMEstimator: Base class for supervised SOMs
        
            - SOMRegressor: Regression SOM
            - SOMClassifier: Classification SOM
        
        :License:
            `3-Clause BSD license <LICENSE>`_
        
        :Author:
            `Felix M. Riese <mailto:github@felixriese.de>`_
        
        :Citation:
            see `Citation`_ and in the `bibtex <bibliography.bib>`_ file
        
        :Documentation:
            `read the docs <https://susi.readthedocs.io/en/latest/readme.html>`_
        
        :Paper:
            `arXiv:1903.11114 <https://arxiv.org/abs/1903.11114>`_
        
        
        Installation
        ------------
        
        With PyPi:
        
        .. code:: bash
        
            pip3 install susi
        
        
        Manually:
        
        .. code:: bash
        
            git clone https://github.com/felixriese/susi.git
            cd susi/
            python setup.py install
        
        .. role:: bash(code)
           :language: bash
        
        .. role:: python(code)
           :language: python3
        
        **Dependencies:** Python 3 with :python:`joblib`, :python:`numpy`, :python:`scikit-learn` and :python:`scipy`.
        
        Usage
        -----
        
        Regression in  :bash:`python3`:
        
        .. code:: python3
        
            import susi
        
            som = susi.SOMRegressor()
            som.fit(X_train, y_train)
            print(som.score(X_test, y_test))
        
        
        Classification in  :bash:`python3`:
        
        .. code:: python3
        
            import susi
        
            som = susi.SOMClassifier()
            som.fit(X_train, y_train)
            print(som.score(X_test, y_test))
        
        Code examples as Jupyter Notebooks:
        
        * `examples/SOMClustering <examples/SOMClustering.ipynb>`_
        * `examples/SOMRegressor_Hyperspectral <examples/SOMRegressor_Hyperspectral.ipynb>`_
        * `examples/SOMClassifier <examples/SOMClassifier.ipynb>`_
        * `examples/SOMClassifier_Salinas <examples/SOMClassifier_Salinas.ipynb>`_
        
        Citation
        --------
        
        The bibtex file including both references is available `here <bibliography.bib>`_.
        
        **Paper:**
        
        Felix M. Riese and S. Keller, "SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python", `arXiv:1903.11114 <https://arxiv.org/abs/1903.11114>`_, 2019. Submitted to an ISPRS conference.
        
        .. code:: bibtex
        
            @article{riesekeller2019susi,
                author = {Riese, Felix~M. and Keller, Sina},
                title = {SUSI: Supervised Self-Organizing Maps for Regression and Classification in Python},
                year = {2019},
                notes = {Submitted to an ISPRS conference},
                archivePrefix = {arXiv},
                eprint = {1903.11114},
                primaryClass = {cs.LG},
                url = {https://arxiv.org/abs/1903.11114}
            }
        
        **Code:**
        
        Felix M. Riese, "SUSI: SUpervised Self-organIzing maps in Python", `10.5281/zenodo.2609130 <https://doi.org/10.5281/zenodo.2609130>`_, 2019.
        
        .. 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}}
            }
        
        
        Change Log
        ==========
        
        [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
        ------------------------
        - [CHANGED] Moved decreasing_rate() out of SOM classes
        - [FIXED] Removed duplicate constructor for SOMRegressor, fixed fit() params
        - [ADDED] Codecov, Codacy
        
        [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
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/x-rst
