Metadata-Version: 2.1
Name: fracridge
Version: 1.3.1
Summary: Fractional Ridge Regression
Home-page: https://nrdg.github.io/fracridge
Author: Ariel Rokem and Kendrick Kay
Author-email: arokem@gmail.com
Maintainer: Ariel Rokem
Maintainer-email: arokem@gmail.com
License: BSD License
Download-URL: https://github.com/nrdg/fracridge
Description: # fracridge
        
        [![DOI](https://zenodo.org/badge/261540866.svg)](https://zenodo.org/badge/latestdoi/261540866)
        
        Is an implementation of fractional ridge regression (FRR).
        
        ## Installation:
        
        ### MATLAB
        
        Download and copy the files from the
        [https://github.com/nrdg/fracridge/tree/master/matlab](MATLAB directory) into
        your MATLAB path.
        
        ### Python
        
        To install the release version:
        
            pip install fracridge
        
        Or to install the development version:
        
            pip install -r requirements.txt
            pip install .
        
        ## Usage
        
        ### MATLAB
        
            [coef,alphas] = fracridge(X,fracs,y,tol,mode)
        
        
        ### Python
        
        There's a functional API:
        
            from fracridge import fracridge
            coefs, alphas = fracridge(X, y, fracs)
        
        Or a sklearn-compatible OO API:
        
            from fracridge import FracRidge
            fr = FracRridge(fracs=fracs)
            fr.fit(X, y)
            coefs = fr.coef_
            alphas = fr.alpha_
        
        ## Online documentation
        
        [https://nrdg.github.io/fracridge/](https://nrdg.github.io/fracridge/)
        
        ## How to cite
        
        If you use ``fracridge``, please cite our paper: "Fractional ridge regression: a fast, interpretable
        reparameterization of ridge regression" (2020)  *GigaScience*, Volume 9, Issue 12, December 2020, https://doi.org/10.1093/gigascience/giaa133 [link](https://academic.oup.com/gigascience/article/9/12/giaa133/6011381).
        
        
        For your convenience, here is the bibtex entry
        
        ```
        
        @ARTICLE{fracridge2020,
          title    = "Fractional ridge regression: a fast, interpretable
                      reparameterization of ridge regression",
          author   = "Rokem, Ariel and Kay, Kendrick",
          journal  = "Gigascience",
          volume   =  9,
          number   =  12,
          month    =  nov,
          year     =  2020
          }
        
        
        ```
        
Platform: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: dev
