Metadata-Version: 2.0
Name: sparsereg
Version: 0.6.4
Summary: Modern sparse linear regression
Home-page: https://github.com/ohjeah/sparsereg
Author: Markus Quade
Author-email: info@markusqua.de
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Requires-Dist: joblib
Requires-Dist: numpy
Requires-Dist: scikit-learn[alldeps] (>=0.19)
Requires-Dist: sympy
Requires-Dist: toolz


sparsereg
=========

.. image:: https://travis-ci.org/Ohjeah/sparsereg.svg?branch=master
    :target: https://travis-ci.org/Ohjeah/sparsereg
.. image:: https://badge.fury.io/py/sparsereg.svg
    :target: https://badge.fury.io/py/sparsereg

**sparsereg** is a collection of modern sparse (regularized) linear regression algorithms.


Implemented algorithms
----------------------

- Mcconaghy, T. (2011). FFX: Fast, Scalable, Deterministic Symbolic Regression Technology. Genetic Programming Theory and Practice IX, 235-260. `DOI: 10.1007/978-1-4614-1770-5\_13 <http://dx.doi.org/10.1007/978-1-4614-1770-5_13>`_

- Brunton, Steven L., Joshua L. Proctor, and J. Nathan Kutz. "Discovering governing equations from data by sparse identification of nonlinear dynamical systems." Proceedings of the National Academy of Sciences 113.15 (2016): 3932-3937. `DOI: 10.1073/pnas.1517384113 <http://dx.doi.org/10.1073/pnas.1517384113>`_

- Bouchard, Kristofer E. "Bootstrapped Adaptive Threshold Selection for Statistical Model Selection and Estimation." arXiv preprint arXiv:1505.03511 (2015).

- Ignacio Arnaldo, Una-May O'Reilly, and Kalyan Veeramachaneni. "Building Predictive Models via Feature Synthesis." In Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO '15), Sara Silva (Ed.). ACM, New York, NY, USA, 983-990. `DOI: 10.1145/2739480.2754693 <http://dx.doi.org/10.1145/2739480.2754693>`_


Installation
------------

``pip install sparsereg``


