Your message dated Mon, 29 Jul 2024 19:00:14 +0000
with message-id <e1syvbs-002zzs...@fasolo.debian.org>
and subject line Bug#903226: fixed in python-gplearn 0.4.2-1
has caused the Debian Bug report #903226,
regarding ITP: python-gplearn -- Genetic Programming in Python with a
scikit-learn inspired and compatible API
to be marked as done.
This means that you claim that the problem has been dealt with.
If this is not the case it is now your responsibility to reopen the
Bug report if necessary, and/or fix the problem forthwith.
(NB: If you are a system administrator and have no idea what this
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--
903226: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=903226
Debian Bug Tracking System
Contact ow...@bugs.debian.org with problems
--- Begin Message ---
Package: wnpp
Severity: wishlist
* Package name : python3-gplearn
Version : 0.3.0
Upstream Author : Trevor Stephens
* URL : https://gplearn.readthedocs.io
* License : BSD 3 clause
Programming Lang: Python
Description : gplearn implements Genetic Programming in Python, with a
scikit-learn inspired and compatible API.
While Genetic Programming (GP) can be used to perform a very wide variety of
tasks, 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.
gplearn retains the familiar scikit-learn fit/predict API and works with the
existing scikit-learn pipeline and grid search modules. The package attempts to
squeeze a lot of functionality into a scikit-learn-style API. While there are a
lot of parameters to tweak, reading the documentation here should make the more
relevant ones clear for your problem.
gplearn currently supports regression through the SymbolicRegressor as well as
transformation for automated feature engineering with the SymbolicTransformer,
which is designed to support regression problems, but should also work for
binary classification. Future versions of the package will expand this class to
support more complicated multi-target classification problems, and much more is
planned too.
--- End Message ---
--- Begin Message ---
Source: python-gplearn
Source-Version: 0.4.2-1
Done: Yogeswaran Umasankar <y...@debian.org>
We believe that the bug you reported is fixed in the latest version of
python-gplearn, which is due to be installed in the Debian FTP archive.
A summary of the changes between this version and the previous one is
attached.
Thank you for reporting the bug, which will now be closed. If you
have further comments please address them to 903...@bugs.debian.org,
and the maintainer will reopen the bug report if appropriate.
Debian distribution maintenance software
pp.
Yogeswaran Umasankar <y...@debian.org> (supplier of updated python-gplearn
package)
(This message was generated automatically at their request; if you
believe that there is a problem with it please contact the archive
administrators by mailing ftpmas...@ftp-master.debian.org)
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Hash: SHA512
Format: 1.8
Date: Sat, 27 Jul 2024 22:00:00 +0000
Source: python-gplearn
Binary: python-gplearn-doc python3-gplearn
Architecture: source all
Version: 0.4.2-1
Distribution: unstable
Urgency: medium
Maintainer: Debian Python Team <team+pyt...@tracker.debian.org>
Changed-By: Yogeswaran Umasankar <y...@debian.org>
Description:
python-gplearn-doc - Documentation for python-gplearn
python3-gplearn - Genetic Programming in Python, with a scikit-learn inspired
API
Closes: 903226
Changes:
python-gplearn (0.4.2-1) unstable; urgency=medium
.
* Initial release. (Closes: #903226)
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