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@@ -0,0 +1 @@ +/structureboost-0.4.3.tar.gz diff --git a/python-structureboost.spec b/python-structureboost.spec new file mode 100644 index 0000000..14d3d05 --- /dev/null +++ b/python-structureboost.spec @@ -0,0 +1,153 @@ +%global _empty_manifest_terminate_build 0 +Name: python-structureboost +Version: 0.4.3 +Release: 1 +Summary: StructureBoost is a Python package for gradient boosting using categorical structure. See documentation at: https://structureboost.readthedocs.io/ +License: MIT +URL: https://github.com/numeristical/structureboost +Source0: https://mirrors.aliyun.com/pypi/web/packages/d5/a2/7375ca57d807136eda7ff601d310c96d8cf9ab6fd146165809b546de8d64/structureboost-0.4.3.tar.gz +BuildArch: noarch + +Requires: python3-pandas +Requires: python3-numpy +Requires: python3-scipy +Requires: python3-matplotlib +Requires: python3-joblib +Requires: python3-ml-insights + +%description +# StructureBoost + +StructureBoost is a package to do Gradient Boosting in a manner that exploits the **structure** of categorical variables. + +Have you ever used "US state" as a variable in a prediction problem and thought "Why can't my algorithm use the geography of the states to make better predictions?" + +Or you've used the month of the year as a predictor, but noticed that January should border December the same way that June borders July. (or hour of the day, or day of the week) + +StructureBoost can help. Read the documentation and references below. Or dive into some [examples](https://github.com/numeristical/structureboost/tree/master/examples) + +## Video Lectures + +There are some explanatory videos on the [Numeristical Youtube Channel](https://www.youtube.com/channel/UCfsbASar8nsLs4NbhQwuaVg) + + +## Documentation +[Read the Docs](https://structureboost.readthedocs.io/) + +## References: + +Lucena, B. "Exploiting Categorical Structure with Tree-Based Methods. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2949-2958, 2020. [http://proceedings.mlr.press/v108/lucena20a/lucena20a.pdf](http://proceedings.mlr.press/v108/lucena20a/lucena20a.pdf) + +Lucena, B. "StructureBoost: Efficient Gradient Boosting for Structured Categorical Variables." [https://arxiv.org/abs/2007.04446](https://arxiv.org/abs/2007.04446) + + + + +%package -n python3-structureboost +Summary: StructureBoost is a Python package for gradient boosting using categorical structure. See documentation at: https://structureboost.readthedocs.io/ +Provides: python-structureboost +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-structureboost +# StructureBoost + +StructureBoost is a package to do Gradient Boosting in a manner that exploits the **structure** of categorical variables. + +Have you ever used "US state" as a variable in a prediction problem and thought "Why can't my algorithm use the geography of the states to make better predictions?" + +Or you've used the month of the year as a predictor, but noticed that January should border December the same way that June borders July. (or hour of the day, or day of the week) + +StructureBoost can help. Read the documentation and references below. Or dive into some [examples](https://github.com/numeristical/structureboost/tree/master/examples) + +## Video Lectures + +There are some explanatory videos on the [Numeristical Youtube Channel](https://www.youtube.com/channel/UCfsbASar8nsLs4NbhQwuaVg) + + +## Documentation +[Read the Docs](https://structureboost.readthedocs.io/) + +## References: + +Lucena, B. "Exploiting Categorical Structure with Tree-Based Methods. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2949-2958, 2020. [http://proceedings.mlr.press/v108/lucena20a/lucena20a.pdf](http://proceedings.mlr.press/v108/lucena20a/lucena20a.pdf) + +Lucena, B. "StructureBoost: Efficient Gradient Boosting for Structured Categorical Variables." [https://arxiv.org/abs/2007.04446](https://arxiv.org/abs/2007.04446) + + + + +%package help +Summary: Development documents and examples for structureboost +Provides: python3-structureboost-doc +%description help +# StructureBoost + +StructureBoost is a package to do Gradient Boosting in a manner that exploits the **structure** of categorical variables. + +Have you ever used "US state" as a variable in a prediction problem and thought "Why can't my algorithm use the geography of the states to make better predictions?" + +Or you've used the month of the year as a predictor, but noticed that January should border December the same way that June borders July. (or hour of the day, or day of the week) + +StructureBoost can help. Read the documentation and references below. Or dive into some [examples](https://github.com/numeristical/structureboost/tree/master/examples) + +## Video Lectures + +There are some explanatory videos on the [Numeristical Youtube Channel](https://www.youtube.com/channel/UCfsbASar8nsLs4NbhQwuaVg) + + +## Documentation +[Read the Docs](https://structureboost.readthedocs.io/) + +## References: + +Lucena, B. "Exploiting Categorical Structure with Tree-Based Methods. Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics, PMLR 108:2949-2958, 2020. [http://proceedings.mlr.press/v108/lucena20a/lucena20a.pdf](http://proceedings.mlr.press/v108/lucena20a/lucena20a.pdf) + +Lucena, B. "StructureBoost: Efficient Gradient Boosting for Structured Categorical Variables." [https://arxiv.org/abs/2007.04446](https://arxiv.org/abs/2007.04446) + + + + +%prep +%autosetup -n structureboost-0.4.3 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-structureboost -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Jun 20 2023 Python_Bot <Python_Bot@openeuler.org> - 0.4.3-1 +- Package Spec generated @@ -0,0 +1 @@ +a40991e923d8429934f8b0f3403e5839 structureboost-0.4.3.tar.gz |