Source: python-apricot-select
Standards-Version: 4.7.4
Maintainer: Debian Python Team <team+python@tracker.debian.org>
Uploaders:
 Michael R. Crusoe <crusoe@debian.org>,
Section: python
Testsuite: autopkgtest-pkg-pybuild
Build-Depends:
 debhelper-compat (= 13),
 dh-sequence-python3,
 dh-python,
 python3-all,
 pybuild-plugin-pyproject,
 python3-setuptools,
 python3-numba,
 python3-numpy,
 python3-scipy,
 python3-sklearn,
 python3-tqdm,
 python3-pytest,
Vcs-Browser: https://salsa.debian.org/python-team/packages/python-apricot-select
Vcs-Git: https://salsa.debian.org/python-team/packages/python-apricot-select.git
Homepage: https://pypi.python.org/pypi/apricot-select/

Package: python3-apricot-select
Architecture: all
Depends:
 ${misc:Depends},
 ${python3:Depends},
Description: submodular selection of representative sets for machine learning models
 apricot implements submodular optimization for the purpose of summarizing
 massive data sets into minimally redundant subsets that are still
 representative of the original data. These subsets are useful for both
 visualizing the modalities in the data and for training accurate machine
 learning models with just a fraction of the examples and compute.