Metadata-Version: 2.1
Name: scikit-discovery
Version: 0.9.18
Summary: A package for Computer-Aided Discovery
Home-page: https://github.com/MITHaystack/scikit-discovery
Author: MITHAGI
Author-email: skdaccess@mit.edu
License: UNKNOWN
Description: <p align="left">
          <img alt="Scikit Discovery" src="https://github.com/MITHaystack/scikit-discovery/raw/master/skdiscovery/docs/images/skdiscovery_logo360x100.png"/>
        </p>
        
        - Explore scientific data with a set of tools for human-guided or automated discovery
        - Design & configure data processing pipelines
        - Define the parameter ranges for your algorithms, available algorithmic choices, and the framework will generate pipeline instances for you 
        - Use automatically perturbed data processing pipelines to create different data products.
        - Easy to use with [scikit-dataaccess](https://github.com/MITHaystack/scikit-dataaccess) for integration of a variety of scientific data sets
        
        
        <p align="center">
          <img alt="Scikit Discovery Overview" src="https://github.com/MITHaystack/scikit-discovery/raw/master/skdiscovery/docs/images/skdiscovery_overviewdiag.png"/>
        </p>
        
        ### Install
        ```
        pip install scikit-discovery
        ```
        
        ### Documentation
        
        See <https://github.com/MITHaystack/scikit-discovery/tree/master/skdiscovery/docs>
        
        ### Contributors
        
        Project lead: [Victor Pankratius (MIT)](http://www.victorpankratius.com)<br>
        Contributors: Cody M. Rude, Justin D. Li, David M. Blair, Michael G. Gowanlock, Evan Wojciechowski, Victor Pankratius
        
        ### Acknowledgements
        
        We acknowledge support from NASA AIST14-NNX15AG84G, NASA AIST16-80NSSC17K0125, NSF ACI-1442997, NSF AGS-1343967, and Amazon AWS computing access support.
        
        ## Examples
        
        Example code with complete science case studies are available as Jupyter Notebooks at: 
        
        [/MITHaystack/science-casestudies](https://github.com/MITHaystack/science-casestudies)
        
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.4
Description-Content-Type: text/markdown
