Artifact python-gplearn-doc_0.4.2-2_all

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deb_control_files:
- control
- md5sums
deb_fields:
  Architecture: all
  Depends: node-mathjax-full, libjs-sphinxdoc (>= 7.3), sphinx-rtd-theme-common (>=
    2.0.0+dfsg)
  Description: |-
    Documentation for python-gplearn
     `gplearn` implements Genetic Programming in Python, with a
     `scikit-learn <http://scikit-learn.org>`_ inspired and
     compatible API.
     While Genetic Programming (GP) can be used
     to perform a `very wide variety of tasks
     <http://www.genetic-programming.org/combined.php>`_, gplearn
     is purposefully constrained to solving symbolic regression
     problems. This is motivated by the scikit-learn ethos, of
     having powerful estimators that are straight-forward to
     implement.
     Symbolic regression is a machine learning
     technique that aims to identify an underlying mathematical
     expression that best describes a relationship. It begins by
     building a population of naive random formulas to represent
     a relationship between known independent variables and their
     dependent variable targets in order to predict new data.
     Each successive generation of programs is then evolved
     from the one that came before it by selecting the fittest
     individuals from the population to undergo genetic operations.
     .
     This package contains documentation for gplearn.
  Homepage: https://github.com/trevorstephens/gplearn
  Installed-Size: '2292'
  Maintainer: Debian Python Team <team+python@tracker.debian.org>
  Multi-Arch: foreign
  Package: python-gplearn-doc
  Priority: optional
  Section: doc
  Source: python-gplearn
  Version: 0.4.2-2
srcpkg_name: python-gplearn
srcpkg_version: 0.4.2-2

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