Metadata-Version: 1.1
Name: streamad
Version: 0.1.0
Summary: Python toolbox for stream anomaly (outlier) detection.
Home-page: https://github.com/Fengrui-Liu/StreamAD
Author: liufr
Author-email: liufengrui18z@ict.ac.cn
License: UNKNOWN
Description: .. image:: ./docs/source/images/logo_htmlwithname.svg
            :align: center
        
        An anomaly detection package for streaming data.
        
        `Documentation <https://www.liufr.com/StreamAD/>`_
        
        
        ------------------------------------------------------
        
        Why StreamAD
        =============
        
        
        Purpose & Advantages
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        StreamAD focuses on streaming settings, where data features evolve and distributions change over time. To prevent the failure of static models, StreamAD can correct its model as needed.
        
        Incremental & Continual
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        StreamAD loads static datasets to a stream generator and feed a single observation at a time to any model in StreamAD. Therefore it can be used to simulate real-time applications and process streaming data.
        
        
        Models & Algorithms
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        StreamAD collects open source implementations and reproduce state-of-the-art papers. Thus, it can also be used as an benchmark for academic.
        
        
        Efficient & Scalability:
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        StreamAD concerns about the running time, resources usage and usability of different models. It is implemented by python and you can design your own algorithms and run with StreamAD.
        
        
        
        Free & Open Source Software (FOSS)
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        `StreamAD` is distributed under `BSD License 3.0 <https://github.com/Fengrui-Liu/StreamAD/master/LICENSE>`_ and favors FOSS principles.
        
        
        ------------------------------------------------------
        
        Installation
        ============
        
        
        The StreamAD framework can be installed via:
        
        
        .. code-block:: bash
        
            pip install -U StreamAD
        
        
        Alternatively, you can install the library directly using the source code in Github repository by:
        
        
        .. code-block:: bash
        
            git clone https://github.com/Fengrui-Liu/StreamAD.git
            cd StreamAD
            pip install .
        
        ------------------------------------------------------
        
        Models
        ===================
        
        
        * `KNN CAD <https://arxiv.org/abs/1608.04585>`_
        * `xStream <https://cmuxstream.github.io/>`_
        * `SPOT <https://dl.acm.org/doi/10.1145/3097983.3098144>`_
        * LSTMAutoencoder
Platform: all
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: BSD License
