Metadata-Version: 2.1
Name: sklearn-sfa
Version: 0.1.3
Summary: A scikit-learn compatible implementation of Slow Feature Analysis
Home-page: https://github.com/wiskott-lab/sklearn-sfa
Maintainer: Merlin Schüler
Maintainer-email: merlin.schueler@ini.ruhr-uni-bochum.de
License: new BSD
Download-URL: https://github.com/wiskott-lab/sklearn-sfa
Description: .. -*- mode: rst -*-
        
        sklearn-sfa - An implementation of Slow Feature Analysis compatible with scikit-learn
        =====================================================================================
        
        .. _scikit-learn: https://scikit-learn.org
        
        .. _documentation: https://sklearn-sfa.readthedocs.io/en/latest/index.html
        
        .. _MDP: https://mdp-toolkit.github.io/
        
        **sklearn-sfa** or **sksfa** is an implementation of Slow Feature Analysis for scikit-learn_.
        
        It is meant as a standalone transformer for dimensionality reduction or as a building block
        for more complex representation learning pipelines utilizing scikit-learn's extensive collection
        of machine learning methods.
        
        The package contains a solver for linear SFA and some auxiliary functions. The documentation_ 
        provides an explanation of the algorithm, different use-cases, as well as pointers how to 
        fully utilize SFA's potential, e.g., by employing non-linear basis functions or more sophisticated 
        architectures.
        
        For use with high-dimensional image data, sklearn-sfa now also includes an experimental implementation of 
        **Hierarchical SFA networks (HSFA)** - please consult the introductory examples in the documentation.
        
        Since sklearn-sfa is in its early stages, we also recommend taking a look at the **Modular Toolkit for Data Processing** MDP_ 
        which provides stable SFA implementations that have stood the test of time.
        
        Installation 
        ------------
        
        The package can be installed via *pip*:
        
        .. code-block:: bash
        
          pip install --user sklearn-sfa
          
        
        Basic usage
        -----------
        
        In Python 3.6+, the package can then be imported as 
        
        .. code-block:: python
        
          import sksfa 
          
        The package comes with an SFA transformer. Below you see an example of initializing a transformer that
        extracts 2-dimensional features:
        
        .. code-block:: python
        
          sfa_transformer = sksfa.SFA(n_components=2)
          
        The transformer implements sklearn's typical interface by providing ``fit``, ``fit_transform``, and ``transform`` methods.
        
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Provides-Extra: tests
Provides-Extra: docs
